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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy complex multi-agent autonomous workflows using orchestration frameworks like LangGraph with 10+ nodes involving collaboration, task decomposition, and parallel execution.
Develop production-grade async Python FastAPI applications integrated with PostgreSQL, Redis, and cloud-based LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4).
Ensure secure, scalable, compliant GenAI solutions with observability, evaluation frameworks, and partnership with cross-functional teams to enhance productivity and automation.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related discipline.
9+ years software engineering experience including 2+ years deploying production LLM-powered applications.
Expert async Python programming skills and experience with agent orchestration frameworks (preferably LangGraph) and cloud LLM services.
Experience with production async web frameworks (FastAPI), containerization (Docker), cloud platforms (AWS/Azure/GCP), and CI/CD pipelines.
Ideal Candidate Profile
Experienced in building autonomous agent systems with advanced design patterns (ReAct, Plan-and-Execute) and tool-calling frameworks including Model Context Protocol and agent-to-agent communication.
Capable of integrating observability and LLMOps tooling (Langfuse, LangSmith) to monitor and optimize large scale AI workflows.
Comfortable working in regulated enterprise environments, collaborating with global distributed teams, and mentoring junior engineers on async programming and LLM best practices.