Lead AI Agent Developer

Responsibilities

• Design, build, and maintain production-grade AI agents and multi-agent workflows for enterprise use cases
• Integrate and operationalize AI/ML models and agent workflows into scalable production systems
• Implement orchestration using Semantic Kernel / Microsoft Agent Framework, LangGraph, LangChain, AutoGen, and/or Strands SDK
• Implement RAG, grounding, and prompt optimization to improve response quality and reduce hallucinations
• Integrate agents with internal and external systems via APIs and connectors
• Design and implement error handling, fallback flows, and escalation paths
• Perform testing and evaluation of agents and automation workflows
• Collaborate with architects and data teams to translate requirements into deployable AI solutions
• Support deployment, CI/CD, and release management (Azure DevOps)
• Monitor and continuously improve agent performance, reliability, and cost efficiency

Languages

Required

• Proficiency in Python development for AI/agent solutions, with solid general scripting ability
• Hands-on experience building agents and multi-agent workflows with one or more orchestration frameworks: Semantic Kernel / Microsoft Agent Framework, LangGraph, LangChain, AutoGen, Strands SDK
• Expertise in Azure AI Foundry for building, deploying, and operating agents at scale (hosted agents, agent service, memory, evaluation)
• Skills in API integration (REST APIs, JSON, authentication via OAuth2 / API keys)

Nice to have

• English proficiency at B2 level or higher
• Experience with multi-cloud agent deployment (e.g., AWS Bedrock via Strands SDK)
• Knowledge of LLMOps / MLOps: monitoring, evals, and cost/latency optimization for AI Agents
• Experience with vector databases, retrieval infrastructure for RAG and Docker
• Skills in Microsoft Graph API integration and delivering in enterprise or regulated/validated environments (e.g., GxP), including governance and observability tooling

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