Artificial Intelligence Engineer

AI Solutions Engineer Position Overview A growing technology team is seeking an experienced AI Solutions Engineer to help drive the adoption of artificial intelligence across multiple business functions. This role will focus on designing, developing, and deploying AI-powered applications that improve operational efficiency, enhance decision-making, and create measurable business value. The ideal candidate combines strong machine learning expertise with hands-on experience in generative AI technologies and enjoys partnering directly with business stakeholders to identify opportunities where AI can streamline processes, reduce manual effort, and improve outcomes. This is an opportunity to work on high-impact initiatives that span several corporate departments while helping shape the organization's AI strategy and best practices. Key Responsibilities AI Solution Development Design and implement AI-driven applications that improve business workflows and employee productivity. Build, deploy, and maintain machine learning and generative AI solutions for enterprise use cases. Develop intelligent systems that leverage large language models, semantic search, and retrieval techniques to deliver actionable insights. Create scalable architectures that support model training, inference, and ongoing optimization. Generative AI & Machine Learning Engineer and refine prompts to improve the quality, reliability, and consistency of AI-generated outputs. Develop retrieval-augmented solutions using embeddings, vector search technologies, and knowledge retrieval frameworks. Train, fine-tune, and adapt machine learning models to address business-specific challenges. Evaluate model effectiveness using appropriate performance metrics and continuously enhance solution accuracy. Business Partnership & Innovation Collaborate with stakeholders across multiple business areas to identify opportunities for AI adoption and process automation. Translate business needs into technical requirements and practical AI solutions. Conduct proof-of-concepts and pilot programs to validate emerging technologies and innovative approaches. Recommend AI-driven improvements that increase efficiency, quality, and operational effectiveness. Governance & Best Practices Promote responsible AI development, including security, privacy, transparency, and governance considerations. Document solution architectures, model performance results, and implementation methodologies. Establish standards and best practices for AI development and deployment. Provide guidance and mentorship to team members on AI technologies and implementation approaches. Required Qualifications 5+ years of experience developing machine learning, artificial intelligence, or advanced analytics solutions. Strong experience building and deploying generative AI applications in production environments. Hands-on expertise with prompt engineering, retrieval-augmented generation (RAG), embeddings, and semantic search. Experience working with cloud-based AI platforms such as Azure OpenAI, Azure Machine Learning, or comparable technologies. Advanced Python development skills. Experience working with both structured and unstructured datasets. Proven ability to evaluate, tune, and improve model performance through testing and iteration. Strong understanding of machine learning lifecycles and model deployment processes. Excellent analytical, problem-solving, and communication skills. Ability to explain complex AI concepts to both technical and business audiences. Preferred Qualifications Experience working with vector databases and semantic retrieval platforms. Knowledge of large-scale data processing environments such as Databricks. Familiarity with AI orchestration frameworks including LangChain or similar technologies. Experience operationalizing AI solutions and supporting production deployments. Understanding of MLOps principles, model monitoring, governance, and version control. Exposure to automation technologies such as Azure Functions, PowerShell, or C#. Familiarity with enterprise data governance, security, and compliance requirements. Experience working within Agile delivery teams. Relevant cloud, AI, or machine learning certifications. Ideal Candidate The ideal candidate is a technically strong AI professional who is passionate about turning emerging technologies into practical business solutions. They possess a blend of machine learning expertise, software engineering skills, and business acumen, allowing them to identify high-value opportunities and deliver AI applications that create meaningful impact across the organization. They thrive in collaborative environments, enjoy solving complex problems, and are motivated by driving innovation through technology.