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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy autonomous multi-agent workflows using frameworks like LangGraph, including complex state machines with conditional routing and error recovery.
Develop production-grade async FastAPI applications integrating PostgreSQL, Redis, cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic, OpenAI GPT-4) and implement real-time streaming and event-driven APIs.
Ensure enterprise-grade security, observability, compliance with data governance and Responsible AI standards, and mentor junior engineers on async Python and LLMOps best practices.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related field.
9+ years of software engineering experience; minimum 2 years in production deployment of LLM-powered applications.
Proven expertise with agentic orchestration frameworks (LangGraph preferred), cloud LLM providers, async Python (asyncio), FastAPI, Docker, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
Work Experience Required: 9+ years software engineering including 2+ years with production LLM deployment
Ideal Candidate Profile
Experienced in designing scalable multi-agent AI systems with complex task decomposition and agent collaboration across multiple domains.
Strong knowledge of agentic design patterns such as ReAct and Plan-and-Execute, LLMOps practices including observability tooling and prompt engineering at scale.
Capable of working in regulated enterprise environments with focus on secure, compliant AI solutions and mentoring junior engineers.