Role & responsibilities

AI Engineer Microsoft Foundry

Key Responsibilities

- Design, develop and deploy Generative AI applications and AI agents using Microsoft Foundry, its SDKs and supported agent development frameworks.
- Evaluate and select appropriate foundation models based on business requirements, quality, latency, cost, security and regional availability.
- Design grounding and retrieval solutions that connect AI applications to approved enterprise knowledge and data sources.
- Build agentic workflows that use tools, APIs and enterprise systems to retrieve information and execute business actions.
- Implement prompt, context and tool orchestration patterns that produce reliable, explainable and maintainable agent behavior.
- Develop automated evaluations for response quality, groundedness, relevance, task completion, tool-call accuracy and content safety.
- Establish release criteria and quality gates for AI applications before deployment to production.
- Implement tracing, logging, monitoring and operational dashboards to assess application quality, latency, token consumption, failures and safety signals.
- Integrate Foundry solutions securely with Azure services, Microsoft 365, Power Platform and other enterprise applications.
- Apply Microsoft Entra ID, Azure role-based access control, managed identities, secrets management and least-privilege principles.
- Package and deploy AI applications using source control, automated testing and CI/CD practices.
- Troubleshoot and optimize AI solutions for performance, scalability, reliability, maintainability and cost.




- Produce technical designs, evaluation reports, operational documentation and reusable engineering components.
- Support UAT, production deployment, incident resolution and continuous improvement of deployed AI solutions.
- Collaborate with Solution Designers, Business Analysts, Security, Architecture and Platform teams throughout the solution lifecycle.

- Monitor developments in Microsoft Foundry, foundation models and agent engineering, and assess their relevance for enterprise adoption.

Role Specifications: **

Academic / Professional Qualifications

- Bachelors degree or equivalent professional degree in computer science of Information Technology

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Work Experience

- Minimum 5 years of skilled experience in software, cloud, data or AI engineering, including hands-on delivery of enterprise Generative AI solutions.
- Demonstrated experience designing, developing and deploying AI applications using Microsoft Foundry or comparable Azure-based AI services.
- Proven delivery experience in one or more of the following areas: enterprise grounding and retrieval, AI agents and tool integration, or model-powered applications.
- Experience integrating AI solutions with enterprise data sources, APIs, Azure services and business applications.
- Experience in applying software engineering practices including source control, automated testing, CI/CD and production support.
- Experience implementing operational controls for AI solutions, including evaluation, telemetry, tracing or monitoring.

📌 Azure+AIFoundry - Agentic MLOPS (Bengaluru)
🏢 Capgemini
📍 Bengaluru