AI Engineer
On-siteIndia, Texas, United States
Job Summary
Build and deploy AI agents and multi-agent systems on Azure using composable patterns and MCP servers to connect agents to internal data sources and enterprise workflows. Design orchestration patterns, tool integrations, and RAG pipelines while developing prompt engineering and evaluation workflows with automated eval loops. Construct APIs for agent integration with enterprise platforms like M365 Copilot and Teams, and implement data pipelines for unstructured data including transcripts and support interactions. Set up CI/CD, responsible AI controls, and production monitoring using agentic dev tools as your primary development workflow.
Required Qualifications
- 4+ years of software engineering experience
- at least 2+ years building GenAI/LLM-based solutions in production environments
- Strong hands-on experience in AI agent development, including building and deploying agents using platforms such as Azure AI Foundry, Microsoft Agent Framework, or similar
- Proven expertise in LLM/GenAI engineering, including prompt engineering, model selection, evaluation, and structured outputs
- Advanced proficiency in Python, with experience writing production-quality, scalable, and well-tested code
- Experience designing and building RESTful APIs for enterprise-grade applications
- Strong understanding of Azure cloud infrastructure, including deployment pipelines, identity, and search services
- Experience building RAG pipelines, orchestration patterns, and tool integrations
- Hands-on experience working with AI-native developer tools such as GitHub Copilot CLI, Claude Code, Cursor, or similar
- Ability to build and manage data pipelines for unstructured data (e.g., transcripts, support interactions)
- Experience implementing CI/CD pipelines, monitoring, and responsible AI practices
- Demonstrated experience in building real AI systems (not just API integrations)
Desired Qualifications
- Experience with MCP server development or similar agent-tool integration protocols
- Exposure to LLM/ML Ops, including evaluation frameworks and automated testing loops
- Familiarity with PySpark, NLP pipelines, or large-scale data processing
- Experience with Copilot Studio and Power Platform
- Knowledge of containerization technologies (Docker, Kubernetes)
- Front-end development experience for building AI-integrated user interfaces
- Experience integrating AI solutions with enterprise tools such as Microsoft Teams and M365 Copilot
- Strong understanding of agent evaluation frameworks and automated evaluation workflows
- Full-stack development experience is a plus
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