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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy complex autonomous multi-agent workflows using orchestration frameworks involving task decomposition, conditional routing, and error recovery.
Develop reusable agent node libraries, testing frameworks, and scalable FastAPI applications integrating databases and enterprise services with real-time streaming APIs.
Integrate cloud-based LLM providers and observability tools while ensuring security, compliance, performance monitoring, and mentoring 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 discipline.
9+ years of software engineering experience, including 2+ years in production LLM-powered applications.
Proven expertise in asynchronous Python, production FastAPI, cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4), and agent orchestration frameworks (LangGraph preferred).
Experience with Docker, Git, CI/CD, cloud platforms (AWS, Azure, or GCP), and secure enterprise integration (LDAP, SSO) is mandatory.
Ideal Candidate Profile
Senior engineer with deep expertise in building and scaling autonomous multi-agent AI systems beyond chatbots, including advanced agentic design patterns.
Experienced in managing complex asynchronous applications and cloud integration with strong command of LLMOps, observability tooling, and prompt engineering.
Able to collaborate effectively with globally distributed teams, mentor junior staff, and translate complex business requirements into scalable technical workflows.