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What makes DHL great? Our People! We know each employee's individual contributions make us the #1 Express Delivery and Logistics Company in the world. Distinguished as No. 1 World's Best Workplace™ by Great Place to Work and Fortune Magazine DHL Express is committed to maintaining an environment that empowers every team member to make the greatest possible impact on our business. Our culture is about personal commitment – to our business, to each other and to our global communities. DHL is dedicated to being a great place to work. In addition to competitive compensation packages, our employees enjoy a range of programs, services and benefits that bring the best to their personal lives. Start YOUR career with DHL today… The Application Cloud Engineer is responsible for designing, deploying, and maintaining cloud-based software systems and backend services, bridging the gap between application development and cloud infrastructure. The Application Cloud Engineer will work closely with development teams, system administrators, and IT teams to ensure efficient, scalable, and secure cloud solutions. The Application Cloud Engineer requires expertise in cloud technologies and the ability to optimize resources for performance, cost, and security. Key Accountabilities: Design, implement, and optimize CI/CD pipelines using GitHub Actions and Jenkins (CloudBees) to support continuous integration, delivery, and deployment of Node.js and Angular applications. Build, version, and manage Docker images and associated configuration files (Dockerfiles, Kubernetes manifests, Helm charts, etc.). Deploy and manage applications on Red Hat OpenShift and Azure AKS (Azure Kubernetes Service). Implement and maintain GitOps workflows using Argo (Argo CD / Argo Workflows) for declarative application delivery and continuous deployment. Manage container image repositories and artifact lifecycle using JFrog Artifactory. Lead the migration of on-premises applications to containerized, cloud-native architectures on OpenShift and AKS. Collaborate closely with the firewall/network team to design and implement application inbound CNAMEs, DNS configurations, and related networking requirements. Ensure security best practices across pipelines, images, and runtime environments (image scanning, secrets management, network policies, etc.). Troubleshoot complex issues across the full stack — from pipeline failures and container builds to Kubernetes networking and application performance. Mentor junior engineers, contribute to architectural decisions, and drive continuous improvement of DevOps practices and tooling. Document pipelines, deployment processes, and operational runbooks. Skills/Qualifications: Bachelor's degree in related field 7+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering roles, with significant focus on application deployment and CI/CD. Proven hands-on experience building and maintaining production-grade CI/CD pipelines with GitHub Actions and/or Jenkins (CloudBees). Strong expertise in containerization: writing Dockerfiles, optimizing images, and managing multi-stage builds for Node.js and frontend (Angular) applications. Solid experience deploying and operating applications on Kubernetes platforms, specifically Red Hat OpenShift and Azure AKS. Hands-on experience with Argo (Argo CD preferred) for GitOps-based continuous delivery. Experience using JFrog Artifactory (or similar artifact repositories) for Docker image management and promotion workflows. Practical networking knowledge relevant to application delivery — including DNS, CNAMEs, inbound traffic routing, and collaboration with firewall/network teams. Strong proficiency with Infrastructure as Code and configuration management concepts. Experience migrating legacy/on-premises applications to containerized cloud environments. Excellent troubleshooting skills across build, deploy, and runtime layers. Strong communication skills and ability to work cross-functionally with development, network, security, and platform teams. Experience with Azure networking services and AKS networking models (CNI, Ingress, Application Gateway, etc.) preferred Familiarity with OpenShift-specific features (Operators, Routes, SCCs, etc.) preferred Knowledge of security scanning tools integrated into CI/CD (Trivy, Clair, etc.) and secrets management solutions preferred Experience with Helm, Kustomize, or similar Kubernetes packaging tools preferred Background in Node.js and Angular application build/runtime characteristics preferred Relevant certifications (CKA, CKAD, Azure Administrator/DevOps Engineer, Red Hat OpenShift, etc.) are a plus. Employee Benefits & Incentives DHL Express benefits and incentive offerings are designed to reflect a substantial experience for both employees and their dependents during their career and life journey. The specifics will vary, but wherever you join and in whatever role, you'll find our benefits and rewards are among the best in the industry They include: Competitive Pay Bonus/Incentive Programs Retirement Savings – 401K with company match Medical, Dental, Vision, well-being programs Tuition Reimbursement Generous Paid Time Off – Starting at 4 Weeks (PT/FT) Paid Leave Employee Discount Program Employee Assistance & Work Life Program Outstanding training opportunities DHL is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. The EEO is the Law poster is available here: https://www.eeoc.gov/employers/eeo-law-poster We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Zachary Piper Solutions is looking for a TS/SCI Kubernetes Platform Engineer to join a highly classified government program. This is a full time position and onsite in Dayton, OH at Wright Patterson AFB, OH. Essential Duties of the Kubernetes Platform Engineer: Improve client's environment with current container software. Inform strategy and design sessions during containerization process. Recommend resources to help client manage and securely adopt containers. Support development of critical cloud platforms. Qualifications of the Kubernetes Platform Engineer: 10+ years of experience in platform or systems engineering 5+ years of cloud experience and supporting CI/CD Strong experience with Kubernetes clusters IaC experience with Ansible or Terraform Must be able to obtain and maintain an active TS/SCI. Compensation for the Kubernetes Platform Engineer: $140,000 - $175,000 (based on experience) Comprehensive benefit package; Cigna Medical, Cigna Dental, Vision, 401k w/ ADP, PTO, paid holidays, Sick Leave as required by law, paid holidays This job opens for applications on 10/23/2026. Applications for this job will be accepted for at least 30 days from the posting date. Keywords: 401k, 401k match, pto, paid time off, holiday, medical, dental, health, culture, ts/sci, top secret, government clearance, security clearance, ssbi, secret clearance, dod clearance, department of defense, army, navy, military, marines, air force, YW, yankeewhite, yankee white, yankee-white, telecom, government contracting, govcon, goc con, federal, fed, devops, devops engineer, platform engineer, platform engineering, devsecops, devsecops engineer, systems engineer, system engineer, Kubernetes engineer, Kubernetes consultant, devops consultant, devops platform, ci/cd, Kubernetes cluster, python, bash, ansible, terraform, iac, infrastructure as code, ts clearance, aws eks, eks, calico, cilium, flannel, istio, service mesh, vmware nsx, cloud engineer, cloud engineering

Mission GroqMetal is building the infrastructure platform that turns large-scale physical compute into a reliable, isolated, customer-consumable AI infrastructure. This is a hands-on Senior Staff role: you will write production software as part of a software engineering team. You will lead the design of a Kubernetes-based software platform focused on large-scale AI training and inference workloads. You will be a key technical leader in building the systems that turn cutting-edge physical infrastructure into a stable product. Location: This role will be based in one of our three hiring hubs: the Dallas, San Francisco, or New York City area. The person hired for this role must be based in one of these three areas. You'll have the flexibility to work remotely while we establish our local Groq office, with the expectation that this role will transition to onsite once the office opens. Responsibilities & Opportunities In This Role Design and build core Groq platform systems: APIs, controllers, operators, reconciliation loops, and infrastructure abstractions. Remain deeply hands-on: Write, review, test, debug, and operate substantial production code while providing Senior Staff technical leadership. Embrace the market: Leverage Kubernetes to build a commercial product for AI infrastructure, delivering production-grade Kubernetes services for dedicated customers running large-scale AI training and inference workloads. Build a system, not just deploy technology: Apply distributed-systems principles to partial failure, retries, concurrency, consistency, idempotency, availability, and recovery. Design for stability and robustness: Design stable platform APIs and contracts that decouple the customer experience from changes in backend infrastructure. Collaborate with a team of experts: Work across infrastructure, inference, networking, infosec, and other teams to turn ambiguous platform needs into production systems. Ideal Candidates Have/are Experienced software engineers first: Strong experience designing, implementing, testing, shipping, and maintaining production software. Deep Kubernetes platform engineering experience: Experience with operators/controllers, CRDs, admission control, node lifecycle, cluster services, and production-grade platform design. Strong distributed-systems expertise: Practical experience reasoning about CAP, consensus, leader election, eventual consistency, state reconciliation, fault domains, and recovery. Experience developing infrastructure software: Experience working through a robust SDLC, including design review, automated testing, CI/CD, staged rollout, rollback, observability, and incident learning. Experience delivering Kubernetes as a Service: Practical knowledge and experience gained from delivering Kubernetes, cloud infrastructure, or infrastructure control planes as a commercially critical or externally consumed product is highly valued, but not required. Hands-on experience using coding agents: Experience using tools such as Codex, Claude Code, or similar systems/harnesses in substantive engineering work is highly valued; real-world practice matters more than commercial deployment. Steeped in the domain: Experience at a hyperscaler or neocloud supporting AI workloads or commercializing GPU clusters, with a strong understanding of the operational and product challenges of large-scale accelerator infrastructure. Comfort with ambiguity: Experience with inference platforms, accelerator/GPU infrastructure, device plugins, cloud infrastructure, or customer-facing platform products. Why Join Us Purposeful Hiring: You're not here by accident, and neither is anyone else. Every teammate is handpicked with intention because who we build with matters. Builders Wanted: You're not just riding the rocket ship, you're building it. Your work directly shapes the trajectory of our company. Mission-Driven Work: We're here to make a real impact. Our mission fuels everything we do. Tackling Hard Problems: If easy isn't your thing, you're in the right place. We solve some of the most complex and exciting challenges in our space. Excellence Is The Standard: High performance isn't just encouraged, it's the baseline. And it's contagious. If this sounds like you, we'd love to hear from you! Compensation Groq is committed to providing competitive compensation through our Total Cash philosophy, which incorporates potential bonus value directly into base pay. The total cash salary ranges for this position, which is inclusive of the potential bonus value, is dependent by level: Staff: $270,400 - $365,000 Sr. Staff: $341,400 - $401,600 Individual placement within these ranges is determined by your geographic location, experience, skills, and alignment with internal compensation standards. These ranges are specific to candidates located in the United States. Compensation for international candidates will vary based on local market dynamics. Beyond cash compensation, Groq also offers a Long-Term Incentive (LTI) Program and a robust suite of employee benefits.

About Keycard At Keycard, we're building identity and access infrastructure for the agent-native era, where software isn't static but a dynamic, constantly changing system of AI agents working on behalf of people and businesses. Keycard gives every agent a verified identity and issues short-lived, task-scoped credentials at runtime, so agents can only do what they were asked to do, and every action is fully auditable. We're backed by a16z, Boldstart, and Acrew, and our founding team built and scaled Snyk, Auth0, HashiCorp, and Heroku. The Role We're hiring two staff-level Software Engineers, Infrastructure to own how Keycard is built, shipped, and run. Keycard is a control plane for agents: identity, credential exchange, delegation, policy, and audit. Many of the enterprises adopting it need that control plane inside their own cloud, behind their network controls, with no standing access for us. Bring-your-own-cloud (BYOC) is a product at Keycard, not a services engagement. It's versioned, documented, and held to the same reliability and security bar as our hosted service. You'll own Keycard's build and release systems, our multi-tenant cloud, dedicated deployments, and deployments in customers' cloud accounts. Build common delivery and operating tools across them, with release safety, reliability, cloud cost, and repeatable installs as priorities. You'll work with founders, engineers, product, and customers, and agree escalation and on-call with engineering. We build on AWS (and later GCP and Azure), EKS, Pulumi, and Helm. What You'll Do BYOC product. Own what it's like to install, upgrade, and get support for Keycard in a customer's cloud, from what their security team reviews to how each version is documented. Compatibility. Decide what we support, from clouds, regions, and Kubernetes versions to customer guardrails like SCPs and egress proxies. Set the skew limits and deprecation policy that keep our control plane and customer-hosted deployments compatible. Deployments. Make a new deployment, ours or a customer's, a configuration change: infrastructure as code, account bootstrap, and network patterns like PrivateLink and certificates that work through customer proxies. For example: take a new customer's AWS account to a running, upgradeable deployment with no standing access from us. Releases. Own one pipeline from commit to running deployment, wherever it runs, with the control plane kept separate from the data plane. Get releases to many independently versioned deployments with staged promotion, approval gates, and rollback. Reliability. Set the availability and durability targets we hold ourselves to for the hosted service, with the observability, runbooks, and incident response behind them. Operate customer-hosted deployments without standing access, using audited break-glass. Agent operations. Build agents for the repetitive work: pre-install checks, installs, failed-upgrade triage, and runbook drafts. They run with scoped credentials, every action is audited, and an engineer approves any change to a customer account. Cost per install. Keep each install cheap in engineering time and cloud spend. Decide what's standard, what's configurable, and what we decline, so one customer's request doesn't become the roadmap. Deployment guardrails. Work through reviews with customers' cloud and security teams. With security, set the guardrails for every deployment, from credential scope and isolation to workload identity and PKI, then build and run them. What We're Looking For You build infrastructure as software in Pulumi, Terraform, or CDK, and write the Go or TypeScript tooling around it. You've run Kubernetes and Helm in production. Deep AWS experience, especially IAM and permission boundaries, Organizations and SCPs, and VPC networking. You've run software in accounts you don't control, like customer VPCs, on-prem, or regulated networks, and supported it through upgrades. You've shipped versioned releases that customers upgrade on their own schedule, with a support matrix and deprecations they could plan around. You debug across layers: a hung request that turns out to be a security group rule, a proxy that breaks a TLS handshake, a certificate challenge that can't reach the internet. You've worked directly with customers' platform and security teams, and turned down a one-off when a product change was better. You think in control plane and data plane: you've designed or run systems where the two are separate and upgrade independently. Agents at work. You already use coding agents in infrastructure work and have a clear view of where they're reliable and where a human has to review. Strong Candidates May Also Have Experience building a BYOC, single-tenant, or self-hosted offering at an infrastructure, data, or security company. Experience with cell-based architecture. GCP or Azure alongside AWS, including private connectivity on those clouds. Workload identity and PKI in production: SPIFFE/SPIRE, cert-manager, private CAs. Experience with OAuth, OIDC, or mTLS, and interest in agent protocols like MCP. Your First 90 Days Take a customer-hosted deployment from pre-production to production with the customer. Make the next install need no bespoke work, starting from the templates, bootstrap, and pre-install checks. Ship a release through one delivery pipeline to hosted and customer-hosted deployments, with staged rollout and rollback. Write down availability and durability targets for the hosted service, with the alerts and runbooks behind them. Who Will Love This Job You want to build a product that runs in someone else's cloud and make it as solid as one you host. You'd rather fix the product than repeat a custom install. What we offer Build at the Frontier: Work every day at the frontier of agent-native systems — shipping, inventing, and iterating on technology that hasn't been built before. You'll be given huge autonomy, the opportunity to gain mastery, and the chance to work in a team that holds each other accountable to succeed. Truly Agent-Native Culture: At Keycard, we don't just enable others to adopt agents — we use them ourselves to build. You'll help shape an organization that embeds AI into its foundation as an enduring competitive advantage. Compensation With Upside: Market-competitive salaries and generous equity packages (4-year vest, 1-year cliff) give you the security to focus on building — and the asymmetric upside of ownership in a company chasing a category-defining mission. Comprehensive Benefits & Recharge: Health, dental, vision, and paramedical coverage for you and your family, plus 4 weeks vacation, 11 statutory holidays, and 1 volunteer day annually. We encourage at least 2 weeks off each year to fully recharge. Tools That Keep You Ahead: A new MacBook Pro, a $500 stipend for peripherals, and the best AI tools available so you can work at the forefront of agent-native workflows. Remote-First Flexibility: We are a remote-first team prioritizing asynchronous collaboration, with hiring focused in North and South America. Work where you're strongest — we just want the best.

Senior Software Engineer – Kubernetes Operators & Controllers Location: Dallas, TX Preferred Work Arrangement: Hybrid, 3 Days Onsite / 2 Days Remote Remote Flexibility: Full remote may be considered for the right candidate Relocation: Available for qualified non-local candidates Employment Type: Direct Hire Overview Our client is seeking a Senior Kubernetes Engineer to design and build the software powering a next-generation GPU-accelerated compute platform supporting AI, machine learning, LLM, and HPC workloads. This is a software development role focused on Kubernetes , not a traditional DevOps, SRE, or Kubernetes administration position. The core focus is building Kubernetes-native software including custom operators, controllers, CRDs, APIs, schedulers, and internal platform services used to orchestrate large-scale GPU infrastructure. The ideal candidate is a strong developer who understands Kubernetes internals and has experience building software on top of Kubernetes, not simply deploying applications or maintaining clusters. Key Responsibilities Develop Kubernetes-native software using Go, Python, or similar languages. Build custom operators, controllers, CRDs, APIs, and platform services. Extend Kubernetes to support GPU-intensive AI/ML and HPC workloads. Develop automation for cluster provisioning, lifecycle management, scheduling, and infrastructure orchestration. Build GPU scheduling, allocation, workload placement, and resource-isolation capabilities. Integrate NVIDIA technologies including GPU Operator, device plugins, MIG, and DCGM. Develop internal tools and APIs for provisioning and managing GPU compute resources. Improve platform scalability, GPU utilization, workload performance, and reliability. Integrate Kubernetes with high-performance networking, storage, and bare-metal infrastructure. Build observability and automated remediation capabilities for distributed compute environments. Required Qualifications Strong software development experience with Go, Python, or another modern programming language. Hands-on experience building Kubernetes operators, controllers, CRDs, APIs, or similar Kubernetes-native software. Strong understanding of Kubernetes architecture, controllers, reconciliation, scheduling, RBAC, networking, and cluster lifecycle. Experience building platforms or distributed systems on Kubernetes. Experience with GPU infrastructure and NVIDIA technologies. Experience supporting AI/ML, LLM, HPC, or other compute-intensive workloads. Strong Linux and distributed systems knowledge. Experience with Terraform, Helm, Kustomize, Argo CD, Flux, or similar tooling. Ability to troubleshoot across Kubernetes, compute, networking, storage, GPU, and application layers. Preferred Experience NVIDIA GPU clusters. Slurm, Volcano, kube-scheduler extensions, or custom scheduling. CUDA, NCCL, PyTorch, or TensorFlow. InfiniBand, RDMA, RoCE, or other high-performance networking. Bare-metal Kubernetes. Internal developer platforms or self-service infrastructure. AI infrastructure, HPC, cloud infrastructure, or large-scale distributed systems. Ideal Candidate The ideal candidate is a software developer who builds Kubernetes-native systems . This person should be comfortable writing operators, controllers, APIs, schedulers, and automation that extend Kubernetes and manage complex GPU infrastructure. Candidates whose background is primarily DevOps, CI/CD, Terraform administration, application deployment, or Kubernetes operations without substantial software development experience are unlikely to be the right fit. Dallas-based candidates are preferred, but full remote may be considered for candidates with exceptional Kubernetes development and GPU infrastructure experience.

Mission GroqMetal is building the infrastructure platform that turns large-scale physical compute into a reliable, isolated, customer-consumable product. As a Kubernetes Platform Engineer, you will build and operate production software within the GroqMetal platform, helping deliver Kubernetes as a commercial product for customers running large-scale AI training and inference workloads. You will own meaningful platform components, work alongside experienced infrastructure engineers, and develop deep expertise in Kubernetes, distributed systems, and large-scale AI infrastructure. Location: This role will be based in one of our three hiring hubs: the Dallas, San Francisco, or New York City area . The person hired for this role must be based in one of these three areas. You'll have the flexibility to work remotely while we establish our local Groq office, with the expectation that this role will transition to onsite once the office opens. Responsibilities & Opportunities In This Role Build production Kubernetes platform capabilities: Implement APIs, controllers, operators, automation, and platform services that support the GroqMetal product by extending Kubernetes. Own components end to end: Take responsibility for well-defined platform capabilities from design and implementation through testing, deployment, operation, and continuous improvement. Operate what you build: Improve reliability, observability, performance, and operational efficiency, and participate in diagnosing and resolving production issues. Build a Kubernetes platform as a commercial platform: Develop capabilities used by dedicated customers running large-scale AI training and inference workloads. Develop distributed systems expertise: Build software that handles retries, failures, concurrency, reconciliation, and changing infrastructure state correctly. Improve the platform: Identify reliability, scalability, and usability problems and work with the team to deliver durable solutions. Collaboration is a core skill: Work within a team of experts to elevate the collective efforts of our team. Collaborate with engineers across infrastructure, inference, networking, infosec, and related teams to integrate platform capabilities holistically. Grow your technical scope: Contribute to design discussions, engineering practices, and technical decisions while developing toward ownership of increasingly complex platform systems. Ideal Candidates Have/are Software engineers first: Experience designing, implementing, testing, shipping, and maintaining production software. Hands-on Kubernetes experience: Experience building or operating Kubernetes-based systems, including areas such as controllers/operators, CRDs, cluster lifecycle, node management, scheduling, networking, or platform services. Production infrastructure experience: Experience operating software in production and debugging problems across application, Kubernetes, networking, compute, and infrastructure layers. Solid distributed-systems fundamentals: An understanding of failure handling, retries, idempotency, consistency, reconciliation, availability, and recovery, with an interest in developing deeper expertise. Experience with disciplined software development: Comfortable with code review, automated testing, CI/CD, observability, deployment, and production operations. Product-minded infrastructure engineers: Experience building Kubernetes, cloud infrastructure, or platform capabilities consumed by customers is highly valued, but not required. Hands-on experience with modern development tools: Experience using coding agents such as Codex, Claude Code, or similar tools in substantive engineering work is valued. Interested in the AI infrastructure domain: Experience with hyperscalers, neoclouds, GPUs, accelerator infrastructure, or AI workloads is valuable, but candidates with strong platform engineering fundamentals can develop this expertise in the role. Comfortable growing through ambiguity: Able to independently solve well-scoped problems, ask good questions when requirements are unclear, and work with senior engineers on broader architectural decisions. Why Join Us Purposeful Hiring: You're not here by accident, and neither is anyone else. Every teammate is handpicked with intention because who we build what matters. Builders Wanted: You're not just riding the rocket ship, you're building it. Your work directly shapes the trajectory of our company. Mission-Driven Work: We're here to make a real impact. Our mission fuels everything we do. Tackling Hard Problems: If easy isn't your thing, you're in the right place. We solve some of the most complex and exciting challenges in our space. Excellence Is The Standard: High performance isn't just encouraged, it's the baseline. And it's contagious. If this sounds like you, we'd love to hear from you! Compensation Groq is committed to providing competitive compensation through our Total Cash philosophy, which incorporates potential bonus value directly into base pay. The total cash salary range for this position, which is inclusive of the potential bonus value, is $184,800 - $302,500, with individual placement determined by your geographic location, experience, skills, and alignment with internal compensation standards. This range is specific to candidates located in the United States. Compensation for international candidates will vary based on local market dynamics. Beyond cash compensation, Groq also offers a Long-Term Incentive (LTI) Program and a robust suite of employee benefits.

At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry—where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 9 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: We are seeking an experienced Senior Cloud Platform Engineer to own the cloud infrastructure and delivery pipeline supporting one of our largest OEM programs. This role is based on-site at the customer's engineering facility, embedded alongside their teams. You will build and operate our GCP-based platform using GitOps and infrastructure-as-code, automate the paths that get software from commit to production, and act as the local owner for cloud access, environment provisioning, and day-to-day operational issues. This is a hands-on role for a broad, self-directed engineer who is comfortable being the on-site technical point of contact and working across organizational boundaries to unblock delivery. Roles and Responsibilities: Own and evolve our GCP cloud platform for the program - GKE, IAM, Vertex, networking, and supporting services - with a focus on reliability, security, and cost. Build and maintain infrastructure as code in Terraform, treating all environment configuration as reviewed, versioned, and reproducible. Operate the platform using GitOps practices (Argo CD, Helm), so that environment state is declarative and every change is traceable to a commit. Design and maintain CI/CD automation that takes services from commit to deployment with minimal manual intervention, including progressive delivery patterns such as blue/green and canary rollouts. Build observability and alerting that gives both Sonatus and the customer a clear view of system health, and lead troubleshooting when things break. Serve as the on-site owner for cloud access and environment issues - coordinating permissions, provisioning, and workflow questions directly with the customer's IT and platform teams. Manage the program's AI resources - model access, GPU and accelerator capacity, quotas, and API keys across Vertex and other model services - and track usage and spend so teams get the capacity they need within budget. Optimize AI model deployment and serving for latency, throughput, and cost, including model selection, right-sizing, batching, caching, and quantization, and measure the results against agreed benchmarks. Automate recurring operational work and reduce toil, so that developer velocity does not depend on manual intervention. Partner with Sonatus engineering teams in California, Ireland, Korea, and India to keep the on-site environment aligned with our broader platform. Requirements: 7+ years of experience building and operating production cloud infrastructure, with a strong DevOps, platform engineering, or SRE background. Deep, hands-on experience with Google Cloud Platform (GKE, IAM, VPC/networking, Cloud Build, or equivalent). Experience with AWS or Azure is welcome, but GCP depth is required. Strong Terraform skills and a track record of managing real production infrastructure as code. Practical experience with GitOps workflows and tooling (Argo CD, Flux, Helm) and a preference for declarative, version-controlled operations. Solid Kubernetes and containerization experience - deploying, scaling, securing, and debugging real workloads. Strong automation and scripting ability (Python, Go, or Bash) and a bias toward eliminating manual steps. Experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar). Comfort operating independently in a customer environment: strong communication, sound judgment on what to escalate, and the credibility to work directly with a partner organization's engineering and IT teams. Experience with ML or AI workloads running on cloud infrastructure. Nice to have: Experience working embedded at, or delivering into, a large enterprise or automotive customer environment. Familiarity with cloud cost management and FinOps practices. Security and compliance experience in a regulated or enterprise setting. Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $137,000—$175,000 USD

Responsibilities Design, develop, and maintain reusable Terraform modules for enterprise cloud environments. Implement Infrastructure as Code (IaC) best practices across development, testing, staging, and production environments. Provision and manage GCP infrastructure using Terraform and automation frameworks. Build complete cloud environments from scratch using GCP services and infrastructure automation. Design, deploy, and manage cloud-native solutions leveraging GCP services. Configure and maintain Cloud Run, BigQuery, Cloud Storage, Firestore, IAM, Secret Manager, and Load Balancing services. Develop and maintain CI/CD pipelines for infrastructure and application deployments. Experience in GCP-native data platforms (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer Implement infrastructure versioning, automated code reviews, governance controls, and deployment strategies. Ensure platform reliability, scalability, high availability, and disaster recovery readiness. Configure and manage networking components including VPCs, Subnets, Firewall Rules, Private Connectivity, DNS, and SSL Certificates. Manage Identity and Access Management (IAM), Service Accounts, and security controls. Implement monitoring, alerting, logging, and observability solutions using Cloud Monitoring and related tools. Experience building APIs and data connectors (Python, Cloud Functions, Cloud Run) that serve downstream applications or AI/ML systems Proficiency with IaC (Terraform) and CI/CD (Cloud Build, GitHub Actions, or equivalent) for pipeline deployment Experience with GCP IAM, VPC networking, and container platforms (GKE, Cloud Run) Troubleshoot production issues and execute root cause analysis for critical incidents. Develop operational runbooks, architecture documentation, and support procedures. Collaborate with Data Engineering and AI/ML teams to build secure and scalable data and AI platforms. Support infrastructure required for Vertex AI Agent Engine, Vertex AI Search, Model Armor, and AI-driven workloads. Implement security, compliance, and governance standards across cloud environments.

Promevo, LLC was founded in 2006 by a group of experienced systems integration, application development, and systems administration specialists in Cincinnati, OH. We are Promevo! The name Promevo is derived from the Latin words promoveo, meaning "to move ahead" and promereo, meaning "to earn". It's our name, but it's also our purpose. We move clients ahead in technology, enabling their competitive advantage and we earn their trust with our technical excellence and dedication to their success. We believe that digital solutions shouldn't be something our clients need to adapt to, instead we make digital solutions adapt to client needs. Promevo is a Google Premier Partner for Google Workspace, Google Cloud, and Google Chrome, specializing in helping businesses harness the power of Google and the opportunities of AI. From technical support and implementation to expert consulting and custom solutions like gPanel, we empower organizations to optimize operations and accelerate growth in the AI era. In addition to Google technology, Promevo's SaaS Platform (gPanel) provides our clients with a centralized user management interface providing administrators with visibility and control over all of their users' data and settings with its robust suite of security features. We walk alongside our clients to help them achieve their digital transformation and infrastructure goals by providing Professional Services such as migrations, custom app development, fast track deployments, and white glove services. We are seeking a hands-on Cloud Infrastructure Engineer to act as the technical builder responsible for deploying, managing, and automating complex Google Cloud solutions for both internal and external client projects. In this role, you will work across a wide variety of cloud domains—including networking, compute, storage, and CI/CD—while ensuring that every environment you build is inherently secure. Beyond deploying core infrastructure using Infrastructure as Code (IaC), you will be instrumental in configuring the critical identity, access, and logging foundations required for enterprise-grade, secure-by-design deployments. By joining the Promevo Team, you will find that our company culture is at the heart of our success. Promevo's core values center around building trust, investing in care of each other, owning our work, respecting our differences, and engaging in positive attitudes. By living out these values each day, we build supportive teams that nurture development and growth, both individually and professionally. Our Promevo team members are committed to living out the core values below: Build and Extend Trust – Show respect and listen. Do what you say you will do. Be transparent and dependable. Keep it Human – Invest in relationships. Show empathy. Do right by others. Take care of yourself, your family, and each other. Own It – Become an expert in your role. Own the outcome. Finish what you start. Answer for the results. Differences Make Us Stronger – Respect Differences. Seek to include different perspectives. Learn from each other. Attitude is Contagious – Be fully engaged. Take pride in what you do. Spread your positivity. Courage. Energy. Passion. Purpose. Duties and Responsibilities: Core Infrastructure & Automation Infrastructure Deployment: Design, build, and maintain highly available GCP architectures (Compute Engine, Kubernetes Engine, VPCs, Cloud Storage) using Infrastructure as Code (primarily Terraform). Automation & CI/CD: Assist in building and maintaining deployment pipelines to automate infrastructure provisioning and application rollouts. GCP Project Provisioning: Set up foundational cloud environments, including establishing organizational policies, creating logical folder structures, and configuring baseline resource hierarchies. Identity, Access & Security Federated Identity Management: Configure and troubleshoot integrations and establish Google Workforce Identity Federation to allow external IdPs secure access to GCP resources. Security Controls: Implement robust IAM and security controls, ensuring least-privilege access across service accounts, users, and groups. Network Security: Configure firewalls, VPC peering, Cloud NAT, and basic network security protocols to protect client workloads. Observability & Operations Monitoring & Logging Setup: Deploy comprehensive observability tools using Cloud Monitoring to ensure system health, performance, and uptime. Audit & Compliance: Configure Cloud Logging to capture, route, and retain system and security events, ensuring centralized audit trails for compliance. Troubleshooting: Act as an escalation point to diagnose and resolve complex infrastructure, network, and IAM-related issues. Skills and Qualifications: Requires an BA/BS degree in Information Technology, Computer Science or related field of study or equivalent experience Experience: 3+ years of hands-on experience provisioning and managing infrastructure on Google Cloud Platform (GCP). Core GCP Knowledge: Strong understanding of fundamental GCP services (VPC Networking, Compute Engine, Cloud Storage, Load Balancing). Infrastructure as Code (IaC): Proficient in writing and deploying infrastructure using Terraform. Identity & Security: Practical experience configuring IAM roles, organizational policies, and SSO/Identity Federation. Scripting: Ability to write automation scripts in Python, Bash, or Go. Client-Facing Skills: Strong communication skills with the ability to explain technical decisions and infrastructure designs to clients and internal Project Managers. A positive outlook, a passion for development and the ability to work as part of a high-performance team. What Promevo Offers Competitive salary and bonus plan 14 Paid holidays Medical Insurance Dental Insurance, 100% company paid premiums Vision Insurance , 100% company paid premiums Fully Company Paid Short term Disability Insurance Fully Company Paid Long Term Disability Insurance Fully Company Paid Life Insurance and AD&D 401k plan: Promevo offers a Safe Harbor 401K plan for full time employees with immediate eligibility. Promevo matches the first 3% of earnings you contribute at 100% and matches the next 2% of earnings you contribute at 50% Home office setup allowance Cell phone allowance 4 weeks of PTO and a healthy work/life balance Development and Training opportunities to help you grow Promevo LLC is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran disability or genetic information or any other reason prohibited by law in employment.

Responsibilities Design, develop, and maintain reusable Terraform modules for enterprise cloud environments. Implement Infrastructure as Code (IaC) best practices across development, testing, staging, and production environments. Provision and manage GCP infrastructure using Terraform and automation frameworks. Build complete cloud environments from scratch using GCP services and infrastructure automation. Design, deploy, and manage cloud-native solutions leveraging GCP services. Configure and maintain Cloud Run, BigQuery, Cloud Storage, Firestore, IAM, Secret Manager, and Load Balancing services. Develop and maintain CI/CD pipelines for infrastructure and application deployments. Experience in GCP-native data platforms (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer Implement infrastructure versioning, automated code reviews, governance controls, and deployment strategies. Ensure platform reliability, scalability, high availability, and disaster recovery readiness. Configure and manage networking components including VPCs, Subnets, Firewall Rules, Private Connectivity, DNS, and SSL Certificates. Manage Identity and Access Management (IAM), Service Accounts, and security controls. Implement monitoring, alerting, logging, and observability solutions using Cloud Monitoring and related tools. Experience building APIs and data connectors (Python, Cloud Functions, Cloud Run) that serve downstream applications or AI/ML systems Proficiency with IaC (Terraform) and CI/CD (Cloud Build, GitHub Actions, or equivalent) for pipeline deployment Experience with GCP IAM, VPC networking, and container platforms (GKE, Cloud Run) Troubleshoot production issues and execute root cause analysis for critical incidents. Develop operational runbooks, architecture documentation, and support procedures. Collaborate with Data Engineering and AI/ML teams to build secure and scalable data and AI platforms. Support infrastructure required for Vertex AI Agent Engine, Vertex AI Search, Model Armor, and AI-driven workloads. Implement security, compliance, and governance standards across cloud environments.

Responsibilities Design, develop, and maintain reusable Terraform modules for enterprise cloud environments. Implement Infrastructure as Code (IaC) best practices across development, testing, staging, and production environments. Provision and manage GCP infrastructure using Terraform and automation frameworks. Build complete cloud environments from scratch using GCP services and infrastructure automation. Design, deploy, and manage cloud-native solutions leveraging GCP services. Configure and maintain Cloud Run, BigQuery, Cloud Storage, Firestore, IAM, Secret Manager, and Load Balancing services. Develop and maintain CI/CD pipelines for infrastructure and application deployments. Experience in GCP-native data platforms (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer Implement infrastructure versioning, automated code reviews, governance controls, and deployment strategies. Ensure platform reliability, scalability, high availability, and disaster recovery readiness. Configure and manage networking components including VPCs, Subnets, Firewall Rules, Private Connectivity, DNS, and SSL Certificates. Manage Identity and Access Management (IAM), Service Accounts, and security controls. Implement monitoring, alerting, logging, and observability solutions using Cloud Monitoring and related tools. Experience building APIs and data connectors (Python, Cloud Functions, Cloud Run) that serve downstream applications or AI/ML systems Proficiency with IaC (Terraform) and CI/CD (Cloud Build, GitHub Actions, or equivalent) for pipeline deployment Experience with GCP IAM, VPC networking, and container platforms (GKE, Cloud Run) Troubleshoot production issues and execute root cause analysis for critical incidents. Develop operational runbooks, architecture documentation, and support procedures. Collaborate with Data Engineering and AI/ML teams to build secure and scalable data and AI platforms. Support infrastructure required for Vertex AI Agent Engine, Vertex AI Search, Model Armor, and AI-driven workloads. Implement security, compliance, and governance standards across cloud environments.

Responsibilities Design, develop, and maintain reusable Terraform modules for enterprise cloud environments. Implement Infrastructure as Code (IaC) best practices across development, testing, staging, and production environments. Provision and manage GCP infrastructure using Terraform and automation frameworks. Build complete cloud environments from scratch using GCP services and infrastructure automation. Design, deploy, and manage cloud-native solutions leveraging GCP services. Configure and maintain Cloud Run, BigQuery, Cloud Storage, Firestore, IAM, Secret Manager, and Load Balancing services. Develop and maintain CI/CD pipelines for infrastructure and application deployments. Experience in GCP-native data platforms (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer Implement infrastructure versioning, automated code reviews, governance controls, and deployment strategies. Ensure platform reliability, scalability, high availability, and disaster recovery readiness. Configure and manage networking components including VPCs, Subnets, Firewall Rules, Private Connectivity, DNS, and SSL Certificates. Manage Identity and Access Management (IAM), Service Accounts, and security controls. Implement monitoring, alerting, logging, and observability solutions using Cloud Monitoring and related tools. Experience building APIs and data connectors (Python, Cloud Functions, Cloud Run) that serve downstream applications or AI/ML systems Proficiency with IaC (Terraform) and CI/CD (Cloud Build, GitHub Actions, or equivalent) for pipeline deployment Experience with GCP IAM, VPC networking, and container platforms (GKE, Cloud Run) Troubleshoot production issues and execute root cause analysis for critical incidents. Develop operational runbooks, architecture documentation, and support procedures. Collaborate with Data Engineering and AI/ML teams to build secure and scalable data and AI platforms. Support infrastructure required for Vertex AI Agent Engine, Vertex AI Search, Model Armor, and AI-driven workloads. Implement security, compliance, and governance standards across cloud environments.