Design and build advanced AI systems powered by large language models (LLMs)
Develop and integrate agent workflows using LangGraph/LangChain frameworks
Implement production-grade APIs with FastAPI to support scalable deployments
Collaborate with cross-functional teams (data scientists, ML engineers, product managers) to deliver end-to-end AI solutions
Optimize performance, reliability, and scalability of AI-driven applications
Stay current with emerging AI/ML technologies and contribute to innovation initiatives.

Requirements

Strong hands-on experience with LLM-powered systems (e.g., GPT, Claude, LLaMA, Mistral)
Deep expertise in Python for AI/ML development
Proven experience with LangGraph/LangChain for agent workflow orchestration
Proficiency in FastAPI for building robust, production-ready APIs
Solid understanding of ML lifecycle management , including deployment, monitoring, and scaling
Experience with cloud platforms (Azure, AWS, or GCP) for AI/ML workloads
Strong problem-solving skills and ability to work in fast-paced environments
Preferred Qualifications
Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) for retrieval-augmented generation
Familiarity with MLOps tools (MLflow, Kubeflow, or similar)
Knowledge of prompt engineering and fine-tuning LLMs
Prior work in enterprise AI applications (chatbots, copilots, automation systems).

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

large language modelsPythonLangGraphLangChainFastAPIML lifecycle managementvector databasesMLOpsprompt engineeringfine-tuning

problem-solvingcollaborationadaptability