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About Plane Plane's mission is to build the infrastructure the world's work runs on. Every organization runs on three things: the projects it's driving, the knowledge it keeps, and the requests it fields. Plane brings all three into one open, adaptable platform: simple enough for any team to adopt, dependable enough for organizations to build on. And we are building it for a future where humans and AI agents do that work together. Plane began in public on GitHub at the end of 2022. Since then it has grown into a work management platform used by teams around the world: 55,000+ stars, 5,000+ forks, and a contributor community that reads our code and files our issues. Organizations run Plane as a managed Cloud service, on their own infrastructure, or inside fully isolated environments. Building in the open keeps us close to users and raises the standard for everything we ship. Plane is the #1 work infrastructure in aerospace, defense, financial services, and other regulated industries: organizations whose requirements for control, auditability, and data residency rule most software out. When the strictest buyers pick a system of record, that choice means something. Adoption is growing fastest on Plane Cloud and in sovereign clouds, deployments that keep everything inside a country's own borders and rules. Plane is backed by top investors and built across San Francisco, London, and Hyderabad. We work in tightly knit teams, stay close to users, and care about the visible product as much as the unglamorous details that make software dependable. People own problems end to end, and we add process only when it helps the work. Humans and agents We believe the next decade of work will be done by humans and AI agents together. Not agents replacing people, and not a chat window bolted onto software built for humans clicking around, but both working in one system of action, where an agent's work is as visible and as accountable as a person's. Most software treats AI as a feature. We treat agents as a kind of worker, and that changes what the system underneath has to be. Agents are only as good as the context they can see and the state they are allowed to change, so shared context, explicit state, durable history, and accountable action are not items on our roadmap. They are the product. Plane is built so that when an agent acts, the humans responsible can see what happened, why, and on whose authority, and the record survives. This is what the infrastructure is for: making the future where humans and agents work together useful, legible, and fully within the organization's control. Every role at Plane is some part of building that. About the role Our largest customers do not buy Plane off the shelf. A bank wants it behind their firewall with SSO tied to their identity provider; a defense contractor wants it air-gapped with a migration plan from three legacy tools at once. You will own the technical architecture for these deployments before the contract is signed and after, translating what a customer's infrastructure and compliance team requires into a Plane deployment that actually holds up. You will work directly with sales on the largest deals we run and with engineering when a customer's requirements push past what we support today. This role exists because our regulated-industry customers ask questions our sales team cannot answer alone, and our engineers should not have to answer on every call. What you'll do Own the technical architecture for enterprise and regulated-industry deployments, from the first discovery call through a signed statement of work. Design self-hosted and air-gapped Plane deployments that satisfy a specific customer's security review, not a generic best-practice checklist. Run technical discovery with customers whose infrastructure and compliance teams will pick apart every answer you give, and be right often enough that they trust the next one. Define the migration path when a customer moves off two or three existing tools at once, including what data does not survive the move and saying so up front. Work daily with sales on live deals and with engineering when a customer's requirements expose a real gap in the product, carrying that gap back as a specific, scoped request rather than a vague one. Answer the same security questionnaire in a slightly different format for the fourth time this month, because every regulated buyer's procurement process is its own small bureaucracy and none of them read each other's paperwork. What you'll bring You have designed and defended a technical architecture to a skeptical buyer , and you can walk us through one deal where the customer's own security or infrastructure team changed your design. You understand self-hosted and on-premises deployment beyond a docker-compose file , including networking, SSO and identity federation, and what changes when a customer runs the software instead of you. You can read a security questionnaire or compliance requirement and translate it into an actual deployment decision , not a reassurance. You are comfortable being the technical voice on a sales call , including the parts where the answer is no or not yet. You write technical documentation a customer's own engineers will actually follow , because you will not be in the room when they run it. Nice to haves You have worked pre-sales or post-sales in a solutions architecture, sales engineering, or technical account management role selling to regulated industries. You have contributed to Plane, run it self-hosted, or maintained another open project people rely on. You have shipped or supported deployments into banking, defense, healthcare, or air-gapped environments specifically. You have opinions about how AI agents should be permissioned and audited in an enterprise environment, and can defend them. Tech Backend : Python/Django, Golang, Node.js, Postgres, Redis Messaging : RabbitMQ, Kafka Infrastructure : AWS, Kubernetes, Rancher, self-hosted deployment via Docker and Helm Identity : SAML, OIDC, SCIM Everyday tools : GitHub, Plane (yes, we run on it), Figma, Slack Why Plane? Every company says it is different. We will try evidence instead. The scope is real. We are a passion team serving companies of every size, including some of the largest in the world. Something you ship this month will run inside a Fortune 500 company and a 50-person startup in the same week, and you will hear from both. The constraints make you better. Plane runs in our cloud, in customers' clouds, and on machines that will never touch the internet. Much of the work happens in the open, where the issues, the fixes, and the roadmap conversations are public. Building software that survives all of that is harder than building an ordinary SaaS product, and it is a better education than most companies can offer. The people-and-agents future is being built here, in production. We think humans and AI agents will share one system of action for work. We are building that system now, for customers who already depend on it, and you will work on that problem directly whatever your role. Your name is on the work. The teams are deeply connected enough that credit and responsibility both find you fast. That is some pressure. Mostly it is the fun part. If that sounds like your kind of place, we would like to meet you. Plane is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. Find Jobs in United Kingdom on Arbeitnow

As a Production Engineer, you will play a key role within our Test Engineering team, programming test software and documenting test procedures to scale production of our next-generation drone platforms. In this position, you will take ownership of verification and production test equipment, from defining test concepts to designing automated test solutions, jigs and needle-bed adapters that help us improve yield and reliability. You'll collaborate closely with our software and electronics engineers and OEM partners to enhance test coverage and reduce testing time, driving efficiency across our manufacturing process. This is a hands-on role in a fast-paced, agile environment, offering the opportunity to design creative, practical test solutions from concept through to mass production. This involves balancing the transition from our existing test setups to more scalable and complete solutions in a pragmatic and iterative way for a number of different projects. Beyond test engineering, you'll apply your software expertise across the broader hardware and software team by supporting the engineering validation efforts of new products. You will also visit OEMs to support new product integrations and support small scale engineering runs in person. Responsibilities and Duties Research, design and build test solutions, including auto generated, 3D printed test equipment and CNC milled custom test jigs, and needle-bed adapters to enable low-volume prototyping and mid- to high-volume PCB production. Plan and execute product verification, covering test case definition, execution, analysis, and comprehensive documentation, also for repair guidance. Write Python code and STM32 firmware to test our embedded products from the inside (selftest) and outside (via test fixture). Collaborate with cross-functional engineering teams by offering technical guidance and hands-on support for testing and validation of advanced avionics PCBs and modular systems. Specify and document additional manufacturer tests (like flying probe) to allow for a layered, holistic approach to test coverage. Write Repair Guides that document the error cases and the affected components. Guide manufacturers with new product integrations usually in person in the factory. Manage tracking systems across multiple locations to inspect the product workflow. Support internal CI systems with real hardware to validate test procedures before upgrading test fixtures at OEMs. Qualifications and Skills Bachelor's or Master's degree in Electrical Engineering, Computer Science or a related technical field. Proficiency in modern Python and C/C++ also applied to embedded systems. 5+ years of experience in programming software that runs on real hardware and testing it on real hardware. CAD experience (e.g., Onshape) and soldering skills are required. Practical experience in Linux, microcontroller programming, 3D printing, and related prototyping tools. Pragmatic, solution-oriented mindset. Good verbal and written English communication skills. Benefits Flexible working hours Stock Options Generous holiday allowance Company pension plan Car parking Enhanced maternity & paternity leave Mental health and wellbeing support Learning and development opportunities About Auterion We are building the leading software and electronics platform for AI-powered autonomous systems for enterprise and government customers. Our team is supporting the most important missions and solving the most challenging problems. At Auterion, we bring together the sharpest minds who love to solve the hardest problems. Join a vibrant team built on innovation, openness, and excellence, where you'll be empowered to develop ideas, collaborate across all levels, and make an impact that matters. Find more English Speaking Jobs in Switzerland on Arbeitnow

We're looking for a QA Engineer to join White Circle , an AI Safety company building the safety, reliability, and optimization layer for AI systems through natural-language policies it automatically tests, enforces, and improves at scale. Backed by $70M (Series A) from top funds and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, and others, White Circle processes 100M+ API calls monthly and trains its own LLMs. This is a manual-first product QA role, with automation as a key tool, in a small team where work ships to production fast. You will Manually test new features and fixes across the web platform and APIs in fast release cycles, sometimes as short as one working day. Identify the highest-risk areas, run exploratory, smoke, regression, and integration testing, and give clear release feedback. Write concise test plans and checklists, investigate unexpected behavior, and file reproducible bug reports. Work with engineers and product owners to clarify requirements and improve testability before development is complete. Automate stable, business-critical flows with Playwright and Python, and integrate them into CI/CD. Requirements 2+ years in QA automation, including building frameworks from scratch. Strong Playwright experience for E2E UI testing and scalable test suite design. Clean Python automation code (pytest, fixtures, parametrize). Hands-on CI/CD integration (GitHub Actions, GitLab CI, or similar). Practical use of AI coding agents and LLM-powered developer tools in testing workflows. Fluent English and clear communication. Based in or relocating to Paris or London (hybrid). Bonus Testing AI/LLM products: non-deterministic outputs, confidence scoring, edge-case prompts. Performance or load testing (k6, Locust). API testing tools (Postman, Insomnia, Yaak) or contract testing. Security-aware QA or SOC 2 environments. We offer Competitive salary + equity. Hybrid work from Paris or London, relocation package for Paris. Top-tier medical insurance in France and flexible time off. L&D budget, all hardware and tools you need, plus covered AI agent and IDE subscriptions. Team off-sites twice a year. Find Jobs in France on Arbeitnow

Since 1956 Milani Plumbing Heating & Air Conditioning, Burnaby, Kingsway has been the market leader for plumbing, heating and air conditioning services in the Lower Mainland. With more than 65 years of ongoing success we continue to expand and excel in providing the best for our customers. With more than 120 service trucks on the road, we field a large volume of calls every day from people all over the Lower Mainland that need our help with their plumbing, drainage, heating and air conditioning service. We are looking for an experienced Electrician to undertake a variety of tasks relating to setting up and maintaining electrical infrastructure. You must have experience in some or all of the following: Execute plans of electrical wiring for well-functioning lighting, intercom and other electrical systems Install all electrical related to Air Conditioning Installations Install home automation systems Install solar panels Install electrical apparatus, fixtures and equipment for alarm and other systems Install safety and distribution components (e.g. switches, resistors, circuit-breaker panels etc.) Connect wiring in electrical circuits and networks ensuring compatibility of components Prepare and assemble conduits and connect wiring through them Prevent breakdown of systems by routinely inspecting and replacing old wiring and insulated cables, cleaning circuits etc. Perform effective troubleshooting to identify hazards or malfunctions and repair or substitute damaged units Ensure jobs are properly staged; sign off on job quality checklist. Education, Experience, and Language: You must hold your Electrician Red Seal certificate Proven experience as an electrician minimum 4 years preferably in residential service FSR-B is required Experience in industrial and/or commercial electrical systems is an asset Thorough knowledge of safety procedures and legal regulations and guidelines Clean driving record Milani Electric Ltd. is an equal opportunity employer! While we thank all candidates for their interest, only those who most closely match our requirements will be contacted. #MP01 Job Types: Full-time, Permanent Pay: $45.00-$55.00 per hour Benefits: Company car Dental care Disability insurance Extended health care Life insurance On-site parking Paid time off Licence/Certification: Drivers Licence (required) Red Seal in Electrical (required) * FSR B (required) Work Location: On the road

Your mission You train the technical teams of strategic cloud partners to build, integrate and support AI applications with confidence. Your audience is solution architects, field engineers, developers, technical consultants and sales engineering teams. You take a proven AI curriculum and make it work for cloud partner audiences: real deployment scenarios, partner-specific examples, live troubleshooting. You are the technical face of our client in the room. Your tasks include: Deliver instructor-led bootcamps, technical workshops, train-the-trainer sessions and hands-on labs for cloud partner organisations. Adapt core AI training content for partner audiences such as solution architects, field engineers, developers and partner enablement leaders. Translate AI capabilities into practical cloud scenarios, reference architectures and customer-facing use cases. Lead practical exercises on how to build, integrate, deploy, evaluate and support AI applications in cloud environments. Troubleshoot participant issues live, from lab setup and API calls to code samples and implementation questions. Work with program leadership and partner enablement stakeholders to refine delivery plans and localise examples. Keep delivery quality high across regions, cohorts and groups with different technical maturity. Capture recurring knowledge gaps and recommend improvements to content, labs and facilitation guides. Your profile You move comfortably between developer-level detail, cloud architecture context and an executive-friendly explanation. You are energised by teaching complex material and you earn credibility with engineers by knowing your stuff. Experience & Education More than 5 years of professional experience in technical training, developer education, solution architecture, technical consulting, partner engineering, software development or cloud enablement. Experience delivering technical workshops, bootcamps, labs or train-the-trainer sessions for professional audiences. Strong practical fluency with generative AI, LLM concepts, prompt engineering, APIs, SDKs and modern AI application patterns. Hands-on familiarity with cloud platforms and partner environments such as AWS, Google Cloud, Microsoft Azure or Oracle Cloud. Fluent English; a second language (French, Spanish or German) is a strong plus. Located in or near a major EMEA city with an airport (for example Paris). Willingness to travel for partner workshops and regional programs (approx. 25-35%). Of advantage: familiarity with Amazon Bedrock (AWS Bedrock). Of advantage: experience enabling cloud partners, hyperscalers, systems integrators or partner field organisations. Of advantage: experience building hands-on labs, certification pathways or partner academies. Skills & Attributes Explains cloud and AI concepts clearly to engineers, architects and business stakeholders alike. Facilitates live technical labs and solves setup, code and API issues on the spot. Strong executive presence and professional conduct with senior partner stakeholders. Adapts content and communication style to different proficiency levels, regions and roles. Reads, explains and lightly modifies sample code in Python or JavaScript. Understands RAG, vector search, AI agents and workflow orchestration well enough to teach them. Of advantage: experience with developer relations, sales engineering enablement or solution architect training. Why us? You teach AI to the people who bring it to enterprise customers, with a premium learner experience as the standard. Impact: Your sessions build the technical confidence that drives AI adoption across partner field teams in EMEA. Responsibility: You own the delivery quality of your workshops and represent a leading AI company directly with strategic partners. Dynamics: AI products change fast, and so does your content; you work in a small team that decides quickly. Development: Product training and credentialing are provided, and you grow into a specialist role in a new, high-visibility training program. Benefits Home office option Flexible working hours Fitness subsidy Apple hardware (laptop & iPhone) These are the recruiting steps that await you: Culture Fit - Get to know Rike or Kim from our People team. Learn more about nonplusultra and our culture. Content & Role Fit Interview - Go deeper into the role with Matze Schulz and a technical colleague from OpenAI. Case Study - Work through a practical training scenario together with Matze Schulz and a technical colleague from OpenAI. Find more English Speaking Jobs in France on Arbeitnow

About HappyRobot HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate through voice and email - they make decisions, take action, and run operations autonomously across entire enterprise systems. Born in Y Combinator (S23) and backed by a16z, Base10, Prysm Capital and Eurazeo with over $200M raised, we power critical operations for global enterprises worldwide. Our platform is battle-tested in the most demanding environments, where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto. About the Role As a Customer Support Engineer , you'll be on the front lines of our customer experience. You'll work directly with customers to quickly triage issues, debug problems, and ensure they're getting the most out of HappyRobot's AI platform. This role is a hybrid between technical support and customer engineering: you'll diagnose issues, design and test quick solutions, and collaborate closely with both engineering and product teams to make our platform even stronger. You'll also apply prompt engineering skills to help customers fine-tune their AI workers, ensuring accuracy, reliability, and speed across real-world logistics workflows. This role is ideal for someone with strong technical fundamentals who wants to grow into a more senior customer engineering or product-facing position over time. Tech Profile Comfortable Full-Stack: Python, React, TypeScript, Node.js. Experience managing APIs and integrations with third-party systems. Some exposure to infrastructure and cloud deployments. Familiarity with LLM prompting and tuning of voices/transcribers; eager to experiment and iterate. Strong debugging and problem-solving skills — quick at identifying the root cause of issues. Must Have Excellent written and verbal communication skills in English — able to explain technical concepts clearly to non-technical stakeholders. Strong ability to triage, prioritize, and resolve issues independently under tight deadlines. Curiosity and adaptability: you can learn customer workflows quickly and propose solutions. Self-starter mindset — comfortable working independently, with a bias toward action. Passion for delivering outstanding customer experiences. Why join us? Join a world-class team of engineers and builders. Backed by top investors including a16z, Y Combinator, Base10, Prysm Capital and Eurazeo. Have ownership and autonomy of projects and are encouraged to ship. Comprehensive Benefits including healthcare, dental, vision coverage. Competitive salary + equity in a high-growth startup. Our Operating Principles Extreme Ownership We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting — if something needs fixing, we own it and make it better. This means stepping up, even when it's not "your job." If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don't wait for someone else to solve it — we lead with accountability and expect the same from those around us. Craftsmanship Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for "just fine." We sweat the details because details compound. Whether it's a product feature, an internal doc, or a sales call — we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build — even when nobody's watching. We are "majos" Be friendly & have fun with your coworkers. Always be genuine & honest, but kind. "Majo" is our way of saying: be a good human. Be approachable, helpful, and warm. We're building something ambitious, and it's easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego. Urgency with Focus Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We're running a high-speed marathon — not a sprint with no strategy. Talent Density and Meritocracy Hire only people who can raise the average; 'exceptional performance is the passing grade.' Ability trumps seniority. We believe the best teams are built on talent density — every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players — that's how we win. First-Principles Thinking Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don't copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It's how we build what others think is impossible. The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller. By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer. In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data. If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through ----- subject to the GDPR. For more information, visit https://www.happyrobot.ai/privacy-policy By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described. Find Jobs in Switzerland on Arbeitnow

Forward Deployed Engineer - Mexico About the Company We're partnering with an AI-native operating system for supply chains used by wholesalers, manufacturers, retailers, and traders. The platform integrates logistics and procurement data through connections with internal and external systems, enabling predictive analytics and automated workflows that improve fill rates, reduce inventory levels, and optimize cash-to-cash cycle time. By leveraging predictive analytics and automation, the company helps large enterprises reduce costs, unlock additional revenue, and prevent under- or over-stocking across complex global supply chains. Role Overview The Forward Deployed Engineer (FDE) is the person who makes the platform work in the real world. This role sits at the intersection of engineering, client operations, and AI implementation — and owns the technical execution of how the platform gets built into each client's environment. The FDE works directly with clients and the Implementation team, learns how each client's systems and operations actually run, and builds the integrations, automations, and AI solutions that make the platform mission-critical. This is a first-of-its-kind role at the company — the person who takes it will be defining what forward deployment looks like here. Key Responsibilities Build integrations between the platform and client systems — ERPs, WMS, TMS, data warehouses — writing real code to connect, extract, and transform data across environments Deploy alongside clients in their environment — understand how their teams actually operate, where data breaks, and what needs to be built or configured to run reliably Design, implement, and iterate on AI workflows using the company's platform — agentic flows, prompt engineering, context design, and output evaluation — tuned to each client's specific supply chain use cases Own the reliability, performance, and continuous improvement of live deployments — monitor outputs, identify failure modes, and fix them without waiting to be asked Translate what you build and learn in the field into structured product feedback, technical documentation, and reusable playbooks — so the next deployment starts smarter than the last Profile We're Looking For You build things: Min. 2-4 years of hands-on engineering experience — Python, REST APIs, SQL — and a portfolio of real integrations or systems you've shipped, not just designed You operate in ambiguity: comfortable walking into a client environment without a complete spec, asking the right questions, and figuring out what needs to be built — without waiting for perfect requirements You understand data end-to-end: how it flows across systems, where it breaks, and what it takes to make it clean and reliable enough for AI to use — SQL or equivalent is second nature You have a working understanding of AI and LLMs: enough to design prompts, evaluate outputs critically, and know when a model result looks right but isn't You communicate clearly across audiences: can explain a technical integration to a VP of Operations and write clean documentation for an engineer — in both Spanish and English You own what you ship: high accountability, low ego — you track down the root cause, fix it, and make sure it doesn't happen again Based in LATAM or the US, available to work across time zones and travel to client sites when needed Nice to Have Background in supply chain, logistics, or operations — you'll understand what stockouts, fill rates, and OTIF mean without needing a glossary Experience integrating with enterprise systems like SAP, Oracle, or similar ERPs and WMS platforms Previous experience in a forward-deployed, solutions engineering, or customer-facing technical role Find Jobs in United Kingdom on Arbeitnow

Wer wir sind Die GBC Group GmbH ist eine inhabergeführte IT-Unternehmensgruppe mit über 500 Mitarbeitenden an mehr als 10 Standorten in Deutschland. Nach dem Buy-and-Build-Prinzip vereinen wir 12 spezialisierte Tochtergesellschaften unter einem Dach, jede mit eigener Expertise und einer gemeinsamen Vision. Wir verstehen uns als starker IT-Partner für den deutschen Mittelstand und bieten unseren Kunden ganzheitliche Lösungen entlang der gesamten IT-Wertschöpfungskette: von Managed Services über Cloud-Infrastruktur bis hin zu IT-Security. Was uns antreibt? Der Anspruch, mittelständische Unternehmen mit maßgeschneiderter, zuverlässiger IT pragmatisch und partnerschaftlich nach vorne zu bringen. Dein Wirkungsfeld Als AI Consultant [m/w/d] machst Du aus Geschäftsprozessen belastbare Automatisierungs- und KI-Lösungen. Dein Ausgangspunkt ist dabei nicht das Tool, sondern der Prozess. Du analysierst, wie ein Prozess tatsächlich funktioniert, zerlegst ihn in Trigger, Entscheidungen, Datenflüsse, Ausnahmen und Schnittstellen und identifizierst, wo Automatisierung und KI einen messbaren und sinnvollen Mehrwert schaffen. Anschließend übersetzt Du diese Erkenntnisse in robuste Workflows und AI-gestützte Lösungen. Du verbindest Fachbereiche, IT und Management, triffst technische und konzeptionelle Entscheidungen und sorgst dafür, dass aus einer Idee eine produktiv nutzbare Lösung wird. Deine Aufgaben & Verantwortung Geschäftsprozesse analysieren, strukturieren und Automatisierungspotenziale identifizieren KI- und Workflow-Lösungen mit Tools wie n8n, Make oder Zapier konzipieren und umsetzen Systeme über APIs und JSON verbinden und saubere Datenflüsse sicherstellen LLMs, Prompt Engineering, RAG, Tool Calling und Agentic Workflows sinnvoll in Prozesse integrieren Fachliche Anforderungen in klare technische Lösungen übersetzen Lösungen eigenständig von der Idee bis zum produktiven Einsatz verantworten Ergebnisse messen, bestehende Automatisierungen verbessern und skalierbar machen DSGVO, AI Act und Governance-Anforderungen von Beginn an berücksichtigen Was Du mitbringst Ausgeprägtes Prozessdenken und ein solides Verständnis von Prozessmodellierung Erfahrung mit Low-Code-/No-Code-Automatisierung, idealerweise n8n, Make, Zapier oder Power Automate Solide Grundlagen in Datenhaltung & SQL: Praktische Erfahrung mit relationalen Datenbanken, Datenmodellierung und SQL sowie dem Arbeiten mit JSON-Payloads und Webhooks Verständnis von eventbasierten Architekturen (Event-Driven Workflows), State Management und resilientem Error Handling in verteilten Systemen AI-Assisted Software Development: Erfahrung im schnellen Prototyping und Erstellen leichtgewichtiger Tools/Skripte (z. B. in Python, JavaScript/TypeScript) idealerweise unter Nutzung moderner AI-Coding-Tools (z. B. Claude Code, Cursor) AI-Implementierungswissen: Fundiertes Verständnis von LLM-Architekturen, Embeddings, Vektordatenbanken, Chunking-Strategien für RAG und Structured Outputs Fähigkeit, komplexe Anforderungen zu strukturieren und verständlich zwischen Business und IT zu vermitteln Eigenständige, analytische und lösungsorientierte Arbeitsweise Bereitschaft, Verantwortung für Entscheidungen und Ergebnisse zu übernehmen Du misst Deinen Erfolg an Wirkung und Ergebnissen Sehr gute Deutschkenntnisse in Wort und Schrift (mindestens C1-Niveau) für die Kommunikation mit unseren Kunden Was Dich bei uns erwartet Arbeite von zu Hause oder aus unseren Büros in Bremen, Frankfurt oder Sindelfingen – je nach deiner Preference Du hast Zugang zu modernem Tech-Stack Du bestimmst deine Lösungen – von der Analyse bis zur produktiven Nutzung. Deine Ergebnisse werden direkt im Kundengeschäft sichtbar und messbar Klare Prozesse, definierte Rollen und Unterstützung durch ein erfahrenes Team aus IT, Fachbereichen und Management Wettbewerbsentsprechende Vergütung und Arbeitszeitmodelle, die sich an Leistung und Ergebnissen orientieren Unser Bewerbungsprozess Erstgespräch HR (ca. 30-45 Minuten) Fachliches Interview inkl. praxisnahem Use Case Persönliches Kennenlernen vor Ort Entscheidung & Angebot Referenzgespräche führen wir ausschließlich mit Deiner ausdrücklichen Zustimmung Hast Du Fragen? Bei Fragen oder Anliegen zu Bewerbungen oder zum Bewerbungsprozess kontaktiere gerne unser HR-Team per E-Mail unter oder melde dich telefonisch direkt bei uns: 07031-4146450. Deine Ansprechpartner: Lisa Stöckl Alexander Becker Find Jobs in Germany on Arbeitnow

We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer. The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time performance visualization tools and analyses. Key Responsibilities: 1. Trading Operations and Performance Analysis with AI Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers. Use AI tools to build reporting and analyses on trading performance and perform adhoc business analytics 2. Risk Monitoring & Control Intelligent Risk Management: Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. Develop and maintain sophisticated risk reporting dashboards for the desk. Requirements & Qualifications: Experience: 3+ years in front-office operations, quant development, or a blend of risk management and systems architecture within a financial institution. Technical Stack: Expert proficiency in Python (for AI/ML), and strong SQL skills. Experience building agentic AI workflows is a significant advantage. Financial Acumen: Good understanding of P&L attribution, financial controls, market risk indicators (Greeks, VaR), financial markets and products. Problem Solving: A "systems-thinking" approach to operations—treating every manual task as a bug that needs an automated solution. Capacity: Ability to thrive in a high-intensity environment requiring extended hours when necessary to meet global trading demands. Find more English Speaking Jobs in United Kingdom on Arbeitnow

At 5Plus (part of Pentadoc Group), we build production-grade AI systems that solve real operational problems for our customers. As a Senior AI Engineer (m/f/d), you will take technical responsibility for customer-facing AI solutions — from early design decisions to production deployment and operation. You will design, build, and operate AI applications ranging from LLM-powered workflows (e.g., intelligent document processing, RAG systems) to agentic AI systems that are actively used in customer environments. German language skills at C1 level and above are mandatory for this role. You'll work closely with customers and internal engineers to translate ambiguous requirements into reliable, scalable systems and guide AI-driven product development within customer projects. This role is hybrid , with predominantly remote work and occasional on-site presence at customer locations across Germany and our office in Würzburg, Bavaria. Your profile Several years (3–6) of hands-on experience building and operating AI/ML systems in real-world projects . Solid experience implementing agents on the LangChain stack ( LangGraph , DeepAgents , LangFuse ) in Python , including FastAPI interfaces/integrations (minimum of 3 agents per project) Basic knowledge of AWS (e.g. ECS , CDK , …) Strong Python expertise (app. 5 years) and experience with modern AI/LLM tooling; framework-agnostic mindset. Proven experience with LLM-based systems (e.g., RAG, embeddings, tool usage) and an understanding of trade-offs between quality, cost, latency, and complexity. Ability to work independently in customer-facing environments , taking ownership of technical decisions under uncertainty. Professional communication skills in customer contexts. Residence in Germany . Bonus points to score Deeper experience with agentic architectures (planning, memory, multi-agent coordination). Experience deploying and operating AI services in cloud environments (AWS, Azure, etc.). Contributions to open-source projects, technical writing, or applied research. Your daily business Design and ship end-to-end AI systems, from prototype to production. Build LLM-powered applications (incl. RAG, tool usage, validations) with a focus on reliability and cost-efficiency. Develop and operate agentic AI systems (e.g., planning, tool orchestration, multi-step workflows) with clearly defined safety and integrations into customers' systems Define evaluation strategies (offline + online), including metrics, benchmarks, and monitoring. Optimize system performance across latency, cost, and quality. Take technical leadership within customer project teams , coordinating architecture, implementation, and iteration cycles. Act as a technical point of contact for customers , explaining trade-offs and guiding solution decisions. Work directly with customers and internal teams to turn ambiguous, real-world problems into concrete AI solutions. Contribute to architectural decisions and support less-experienced engineers through technical guidance (no people management). Some of your benefits at 5Plus Real ownership: Build and own AI solutions that go live quickly! Small, experienced team with fast decision-making . Flexible working hours and freedom to choose your workplace . Learning budget and support for conferences and publications . Pentadoc Group offers additional benefits, feel free to check out everything To plan an initial conversation quickly, please make sure your application contains all relevant documentation and information, you'd like to share with us. We look forward to meeting you! Find more English Speaking Jobs in Germany on Arbeitnow

Elliptic is the leader in digital asset decisioning, we have built the most comprehensive platform for efficiently extracting crypto data and intelligence across blockchains with the greatest accuracy. Our platform's unrivalled uptime, scalability, depth and breadth of our data and intelligence means exacting organizations choose Elliptic for their compliance, risk management, intelligence operations and blockchain infrastructure needs. Founded in 2013, Elliptic is headquartered in London with offices in New York, Washington D.C., UAE, Singapore and Tokyo. To learn more, visit www.elliptic.co and follow us on LinkedIn and X . Do you want to lead a data science team on a problem the industry has not solved yet, while still writing code yourself? Are you excited about building the data foundation for how compliance works when the customer is an autonomous agent rather than a person? Are you looking for a values led company where a small team is trusted with a question that matters commercially in months, not years? The impact you will have: You will lead data science inside Elliptic's Intelligence team, alongside Intelligence Collection, Research and Investigations, and Professional Services. This is deliberately a player-coach role with a prospect of scaling a team. At first you will lead a small team of data scientists and you are expected to own the team's direction, performance and growth. You will own the evidence for the models your team builds, and you will represent them at Elliptic's model risk governance forum. This is not a compliance tax bolted onto the technical work: it is the reason institutions trust our outputs. The reason we are hiring a lead as we add more data scientists is that a small team working on an unsolved problem needs someone who intrinsically understands the domain, not a layer of management above it. You will set what this team works on, hire the next people into it, and be the person whose technical judgement the team trusts because you can do the work yourself. What you will do: Lead and grow the team. Set objectives with your data scientists in the context of company strategy, own their performance and development, and be the manager who has the difficult conversation rather than deferring it. Level the team against Elliptic's Intelligence career framework and build real development paths. Hire the next data scientists. Own the hiring process end to end with support: levels, job descriptions, hiring plan, interview panel and bar, and the hiring decision. Team growth to seven to nine people over time depends on you getting this right early. Build the collection for the future of compliance. Take it from a directive to a specification to delivered data: define what good looks like, sequence the work, set the quality bar, and be honest about what the dataset does and does not support. Own model governance for your team's models. Keep the model inventory current and correctly tiered, make sure validation and testing evidence exists at the standard each tier requires, monitor for drift and act on threshold breaches, and submit material changes and production deployments for review with the testing artefacts attached. Own the remediation of issues raised against your models, to agreed deadlines. Lead Elliptic's data science work. Frame the research question, run the first experiments, and form a defensible view of what Elliptic needs to be able to do and by when. Bring that view to Intelligence leadership, the Chief Scientist and Product as a recommendation rather than as an open question. Stay technically hands on. Write code, review your team's work at the level of method rather than output, and make the method calls yourself when they matter. Own the team's existing commitments. The team's current work on clustering, attribution, heuristics and labelling continues to serve the platform. You own its reliability and its trade offs, and you decide what to stop. Work across functions. Partner with Intelligence Collection, Collection Engineering, Research and Investigations, the Chief Scientist, Product and Engineering, so that data science work lands as platform capability rather than as analysis nobody uses. Set the AI working standard for the team. Decide how your team uses AI in its engineering and research workflow, what must be verified and how, and hold the team to it. What you will achieve in the first 6 months: The collection plan delivered at a scale that supports real model or heuristic work, with a documented path to maintaining it. An agreed Elliptic position on the evolution of compliance systems, timed against expected industry demand, with the first capability work either underway or deliberately deferred with stated reasons. At least one data science hire made, and the existing levelled against the career framework with development plans in place. Model governance in good standing for everything your team owns: inventory current and correctly tiered, no overdue validations on the highest tiers, monitoring in place with acted-upon thresholds, and no open issues past their remediation deadline. Data science objectives for Intelligence agreed and delivering, with other functions able to state what they can expect from the team and when. A visible improvement in the reliability or throughput of the team's core output, attributable to a change you made. Technical credibility intact: the team takes your method judgements seriously because you can do the work. You will be a great fit here if you: Want to lead a team without leaving the technical work behind, and can say honestly where you draw that line. Are comfortable being accountable for a question nobody has answered yet, including for saying what you do not know. Treat management as the work rather than as overhead: objectives, feedback, development and difficult conversations included. Treat governance as part of building good models rather than as paperwork that follows them, and would rather surface a problem with your own model than have someone else find it. Are pragmatic about trade offs between rigour and speed, and can explain the trade off you chose. Make other teams more effective rather than treating them as consumers of your team's output. Are curious about how the company operates beyond your own function. Care about the mission of using intelligence to fight financial crime and protect the global financial system. Our ideal candidate has: AI fluency, which is essential for this role. You must be able to demonstrate how you apply AI tools and approaches within a data science workflow: writing and debugging code, exploring unfamiliar data, accelerating pipeline and model work, and automating repetitive tasks. You must also be able to show how you critically evaluate the output, where you would not rely on it, and how you set verification expectations for a team rather than only for yourself. This is assessed in a dedicated stage of the interview process, working with your own tooling. Demonstrated experience managing data scientists or machine learning engineers: setting objectives, owning performance including underperformance, and developing people. You can point to someone whose career changed because of how you managed them. Experience hiring into a technical team, including defining the bar rather than only sitting on panels. Deep, hands on data science and machine learning capability that is current. Strong Python and SQL, and the ability to interrogate large behavioural or transactional datasets yourself and defend your method under challenge. A track record of taking an ambiguous question to a delivered dataset, model or capability, including deciding what was good enough. Experience with a modern data stack comparable to ours: a cloud data lake, Spark or Databricks, and AWS. Clear communication with technical and non technical stakeholders, and the ability to cascade direction to a team so that each person knows why their work matters. Based in Washington, D.C. or willing to relocate there. US citizenship Bonus Points for: Work on agentic systems, LLM agents or autonomous transaction flows, whether in compliance, payments, fraud or infrastructure. Experience building a large dataset or collection from nothing, including the unglamorous parts: schema decisions, quality checks, and maintenance. Blockchain or on chain data experience: clustering, attribution, heuristics, anomaly detection, mempool analysis, or research into privacy preserving systems. Experience in payments, fraud or risk data science, where the cost of a false negative is commercial rather than academic. Having grown a team from a few people to a full department, and being able to describe what broke on the way. A PhD or equivalent research training, or a record of published applied research. Experience in a regulated environment or with model risk management frameworks, whether in financial services, or as a vendor to it, or in another domain with equivalent assurance requirements. Job Benefits > How we work: Hybrid working and the option to work from almost anywhere for up to 90 days per year £500 Remote working budget to set up your home office space > Learning & Development: $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development > Vacation/ Leave: Holidays: 25 days of annual leave + bank holidays An extra day for your birthday Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave and leave. > Benefits: Private Health Insurance - we use Bupa! Full access to Spill Mental Health Support Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries Cycle to Work Scheme We know Diversity and Inclusion is much deeper than just hiring, but it's important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We know incredible people don't all think in the same way. We want to be challenged every day. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work. Find Jobs in United Kingdom on Arbeitnow

At Bumble, we're building the Love Company — a place where healthy, equitable relationships and friendships can start and grow. Machine Learning sits at the heart of that mission, helping us understand what makes a meaningful connection and powering the matching, recommendation and personalisation experiences that bring people together. As our Principal Machine Learning Engineer, Matching & Recommendations , you'll help define the technical and ML strategy behind the next generation of Bumble's recommendation systems. You'll remain hands-on while tackling complex problems across retrieval, ranking, personalisation, experimentation and two-sided marketplace optimisation , partnering across Engineering, Product, Data Science and Analytics to turn ambiguous member problems into scalable ML solutions. You'll lead through technical influence, raise the bar for ML engineering across the organisation, and help us build systems that optimise not simply for engagement, but for better connections and meaningful member outcomes. What you'll do Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, matching, ranking and personalisation across Bumble products, delivering measurable improvements in member outcomes, engagement and safety. Design, develop and deploy production-grade models using modern ML frameworks such as PyTorch , ensuring scalability, reliability and performance in high-traffic environments. Build and deploy production AI agents using foundation models and fine-tuned Large Language Models (LLMs), alongside sub-agents, tools and MCP integrations . Architect end-to-end ML pipelines, integrating large-scale data processing technologies such as Spark and Airflow with model training, evaluation, deployment and monitoring workflows. Define and evolve experimentation strategies, including A/B testing, offline evaluation and online measurement , to continuously improve model performance and product outcomes. Partner cross-functionally with Product, Engineering and Data leadership to translate complex business and member challenges into impactful ML solutions, collaborating with purpose and influencing at senior levels. Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity and continuous learning across Bumble's ML community. Take ownership of complex and ambiguous problem spaces, seeing initiatives through from insight to measurable impact whilst adapting approaches as new information emerges. Champion responsible AI practices , ensuring fairness, transparency, privacy and member safety are considered throughout the design and operation of Machine Learning systems. About you Typically, you will have 10–15 years of relevant experience , although we welcome candidates with alternative backgrounds who can demonstrate equivalent skills, scope and impact. You have deep expertise in Machine Learning, with significant hands-on experience designing, building and deploying large-scale ML systems in production environments . You have strong proficiency in Python and at least one major ML framework, such as PyTorch or TensorFlow , with experience in areas such as recommendation systems, ranking, retrieval, personalisation or NLP. You understand modern recommendation-system approaches and can reason deeply about model architecture, features, loss functions, evaluation methodology, experimentation and the trade-offs between offline performance and online outcomes . You have experience prompting and fine-tuning Large Language Models (LLMs) and building production AI agents using modern agentic architectures and tooling. You have proven experience designing scalable data and ML pipelines using technologies such as Spark, Airflow , or comparable distributed data and orchestration systems. You have demonstrated the ability to operate as a senior individual contributor, setting technical direction and influencing strategy across teams without relying on direct authority . You are comfortable navigating highly ambiguous technical and product problems, balancing immediate delivery with longer-term architectural and ML strategy. You partner effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organisational environments. You have a track record of mentoring and developing other engineers, role-modelling Respect and Excellence whilst helping build inclusive, high-performing teams. You bring strong AI fluency and technical judgement, with the ability to independently design, evaluate and optimise ML systems whilst guiding others in the responsible and effective application of AI. About Us Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. The Bumble platform enables people to build healthy and equitable relationships, through Kind Connections. Founded by Whitney Wolfe Herd in 2014, Bumble was one of the first dating apps built with women at the center and connects people across dating (Bumble Date) and friendship (BFF). BFF is a friendship app where people in all stages of life can meet people nearby and create meaningful platonic connections and community based on shared interests. Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI Fluency AI is important to us. We're excited by people who are curious and experimental, and who think thoughtfully about how AI can amplify their impact and outcomes. We encourage you to use AI responsibly as you prepare your application. Please don't use it to fabricate experiences or answer questions live in interviews. We care deeply about authenticity and want to understand your real skills, judgment and voice, because building a meaningful, genuine connection with you matters to us. Final Compensation Will be determined based on factors such as the selected candidate's qualifications, relevant experience, skill set, and other job-related considerations. Inclusion at Bumble Inc. Bumble Inc. is an equal opportunity employer and we strongly encourage people of all ages, color, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, people with disabilities, and neurodivergent people to apply. We're happy to make any reasonable adjustments that will help you feel more confident throughout the process, please don't hesitate to let us know how we can help. In your application, please feel free to note which pronouns you use (For example: she/her, he/him, they/them, etc). AI in Bumble Inc. Hiring At Bumble, we may use AI tools to support parts of our recruitment process — such as helping us record, transcribe, and summarize conversations, and supporting job alignment by comparing resumes and job descriptions to highlight skills and potential roles that may be a good match. These tools help us work more efficiently and stay focused on you during our conversations. Importantly, all hiring decisions are made by people. AI is used only to support our team's efficiency and improve the candidate experience — not to evaluate or decide on your candidacy. Participation in AI-supported interviews and conversations is completely voluntary and will not impact your candidacy. If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call, or anytime during the interview or conversation. Summaries and related data are retained only as long as needed in line with our internal data retention policies. If at any point you'd like a transcription or summary deleted, please contact your recruiter directly. Fraudulent Candidate Detection Our applicant tracking system analyzes signals relating to device, IP, email, and phone data associated with each application to protect applicants and our hiring process from fraudulent applications. These signals provide indicators for internal review only and do not constitute a definitive determination of identity or intent. No applicant is rejected, advanced, or otherwise affected based solely on this analysis without human review For further information on how we hold and manage your data, please refer to our Privacy Policy . Find more English Speaking Jobs in United Kingdom on Arbeitnow