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Metro location, mid-level (3 years), and in-demand GenAI skills create moderate candidate competition.
Skills are transferable across industries but require GenAI and Databricks experience, creating moderate industry specificity.
Multiple mandatory technical requirements (Databricks, LangChain, FastAPI, Azure) make filters strict.
Design, build, and maintain production-grade GenAI, RAG, and agentic AI applications on Databricks for fleet and shore-based operations.
Develop and optimize multi-step reasoning agentic solutions and pipelines using frameworks like LangChain, LlamaIndex, and Agent Bricks.
Contribute to strategic AI initiatives by evaluating emerging tools, running POCs, shaping architecture, and supporting roadmap planning.
Minimum 3 years of experience in AI/ML, data, or software engineering with hands-on GenAI delivery experience.
Strong experience with Databricks platform including Unity Catalog and vector search.
Proficient in Python programming, solution design, and production-grade software architecture.
Experience with building APIs using FastAPI or similar frameworks and working knowledge of Azure cloud services and PostgreSQL or similar relational databases.
Experienced in end-to-end GenAI and agentic AI system development and operationalization in a production environment.
Skilled in applying observability, evaluation, and performance tuning techniques for LLM/agentic solutions.
Comfortable contributing to both technical execution and strategic AI roadmap development in a technology-driven team.