Back
Metro location, broad LLM/production skillset and reputable employer increase applicant density despite seniority and niche expertise.
Role demands production LLM/LLMOps expertise, making cross-industry transfer moderately constrained.
Explicit 9+ years and specific LLM/production tech requirements make shortlisting highly selective.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and deploy autonomous multi-agent workflows using orchestration frameworks such as LangGraph, CrewAI, Autogen, or similar.
Develop and maintain scalable, reusable agent node libraries, testing frameworks, and production-grade async FastAPI applications integrating databases and external enterprise services.
Lead integration of cloud LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4) and observability platforms for monitoring, security, and compliance in enterprise-grade LLM-powered applications.
Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, Data Science, or related field.
9+ years of software engineering experience with 2+ years in production LLM-powered applications development.
Proven expertise in async Python programming (asyncio, async/await), FastAPI, cloud platforms (AWS, Azure, or Google Cloud), Docker, CI/CD, and LLM orchestration frameworks (e.g., LangGraph).
Experience with integrating LLM providers (AWS Bedrock, Azure OpenAI, Anthropic Claude, OpenAI GPT-4) and observability tools like Langfuse or LangSmith.
Strong in architecting complex multi-agent workflows with advanced agentic design patterns including ReAct and Plan-and-Execute.
Experience in managing or collaborating with offshore technical teams and global stakeholders preferred, especially in life sciences or GPS domains.
Demonstrated ability to lead development of scalable, secure, and performant LLM-powered applications with operational focus on testing, monitoring, and cost optimization.