Description

Key Responsibilities

• Design and implement agent logic and execution steps for complex, multi-step workflows.
• Build agent flows that handle reasoning, tool selection/invocation, and structured response generation.
• Integrate agents with orchestration, monitoring, and MCP layers to ensure reliable operation.
• Ensure agents operate in an assistive, non-autonomous mode with clear reviewability and safety controls.
• Handle retries, failures, and edge cases within agent execution pipelines.
• Support evaluation, tuning, and iterative refinement of agent behavior in production settings.

Qualifications

• 12+ years of software/backend engineering experience with demonstrable leadership on complex systems.
• Strong Python skills and deep hands-on experience building AI agents and agent frameworks (e.g., LangGraph, LangChain Agents, or equivalent).
• Experience designing multi-step, stateful workflows and implementing agent orchestration logic.
• Practical experience with RAG solutions and knowledge-graph integrations, including Azure AI Search and Neo4j.
• Proven ability integrating agents with external tools via APIs and building robust REST API services.
• Background in backend engineering and software engineering best practices for scalable, maintainable systems.
• Nice to have: exposure to enterprise automation platforms

Key Skills

Education

Bachelor's degree