• Translate product specifications into AI service architectures — decompose business intent into agent workflows, data source integrations, and scalable
service designs.
• Build agentic AI workflows using Azure AI Foundry Agent Service and Microsoft Agent Framework, including multi-agent coordination, tool integrations,
and agent lifecycle management.
• Develop and iterate on LLM-based solutions including prompt engineering, model selection, cost/token optimization, and RAG pipeline design.
• Build evaluation systems including rubrics, golden datasets, and judge agents to validate agent correctness and safety before production deployment.
• Write production-quality C# and Python with test-driven development, ensuring services meet reliability, performance, and security standards.
• Deploy services using CI/CD pipelines, feature flags, and staged rollouts with full production observability (tracing, logging, metrics).
• Implement secure service patterns including RBAC, Managed Identities, and secrets management.
• Integrate agents with Azure data sources and cloud-native services to ground agent responses in real-time signals.
• Apply Responsible AI practices across all agent development, ensuring outputs are safe, fair, and compliant.
• Execute reliably within sprint and co-development commitments across ACES and partner engineering teams.
• Own the end-to-end lifecycle of AI service components, including design, development, testing, deployment, monitoring, and incident response.