AI Engineer

Design and build AI agents using Azure AI Foundry and related Microsoft AI technologies.

Integrate agents with enterprise tools including Microsoft Foundry Data Agents , file and vector search systems, APIs, external apps, and MCP servers.

Develop, maintain, and optimize agent instructions, prompts, workflows, and tool integrations.

Evaluate agent quality through structured testing, benchmarking, and validation methodologies.

Deploy, version, monitor, and support agents in production environments.

Work directly with Microsoft Fabric environments including warehouses, Lakehouse, SQL endpoints, semantic models, and ontologies.

Evaluate and recommend retrieval strategies, balance accuracy, performance, maintainability, and cost optimization.

Implement governance and security controls including least-privilege access models, service principals, RBAC, and secure authentication methods.

Partner with infrastructure, security, and compliance teams to ensure agents meet organizational standards.

Understanding of data modelling and exposure to ETL/ELT development in Fabric or Databricks

Comfortable implementing pro-code agentic solutions and acting as a subject matter expert for Agentic AI solutions within the Information Management team.

What you bring to the table

Related post-secondary education in Computer Science, Engineering, Data Science, Information Systems, or related discipline.

2–5+ years of experience in software engineering, analytics engineering, data engineering, AI engineering, or related technical roles.

Hands-on experience with Azure AI Foundry , including agents, tool integration, orchestration, and AI application development or similar platforms.

Experience building CI/CD pipelines and implementing artifacts compatible with CI/CD processes along with Git and Azure Devops.

Hands-on experience with Microsoft Fabric, including Data Agents, Warehouses, Lakehouses, SQL Endpoints, Semantic Models, and enterprise data access patterns.

Strong proficiency in Python and SQL .

Knowledge of Azure Identity and Security , including Entra ID, Service Principals, RBAC, Key Vault, and token-based authentication.

Strong understanding of modern AI and LLM concepts including prompting, retrieval-augmented generation (RAG), tool use, context management, and agent design.

Strong ability to bridge business needs and technical solutions, with experience presenting to executive stakeholders.