Back
Strong employer brand, metro location, and specialized ML role create moderate applicant competition.
Highly specialized agentic LLM and LLMOps skills limit cross-industry transferability.
Explicit 8+ years plus 2+ years LLM production experience and specific tech requirements drives high strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect and develop autonomous multi-agent systems with graph-based orchestration workflows integrating LLM reasoning, real-time data, and enterprise security.
Design and implement complex agent workflows with conditional routing, parallel execution, and tool-calling for analytical and diagnostic tasks.
Build and deploy async Python backend systems (FastAPI) with real-time streaming, robust error handling, and cloud LLM integration using Docker and CI/CD.
Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
8+ years of software engineering experience with 2+ years building production LLM-powered applications.
Expert-level async Python programming skills and experience with agentic orchestration frameworks (preferably LangGraph).
Experience with FastAPI, cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic, or OpenAI), Docker, and cloud platforms (AWS, Azure, or Google Cloud).
Experienced in designing complex autonomous agent workflows beyond simple chatbots, including multi-step tasks and tool-calling integration.
Skilled in managing end-to-end LLMOps including observability, performance optimization, and evaluation frameworks.
Comfortable collaborating cross-functionally with globally distributed teams, mentoring engineers, and contributing to architecture and documentation.