Partner with stakeholders to define problem statements, success metrics, and solution concepts; deliver end-to-end implementations from POC to scaled enterprise deployment (security, governance, reliability, cost).
Design and build advanced GenAI applications including RAG, agentic RAG, and multi-agent orchestration, integrating into existing enterprise systems and workflows.
Build working solutions from the ground up in Python (services/APIs, integrations, testing, and telemetry) to demonstrate value quickly; iterate with users to validate usability and outcomes, then harden for production.
Work across AWS, OpenAI services, Databricks, Dataiku, and SQL ecosystems to enable data access, orchestration, deployment, and monitoring.

Requirements

Bachelors degree with 7+ years in solution architecture and/or senior engineering roles delivering enterprise systems.
Masters degree with 5 years preferred or education equivalency with over 10 years of related industry experience may be considered
2+ years of experience delivering Generative AI solutions in an enterprise environment, including taking solutions from prototype to production-scale deployment.
Strong hands-on Python experience delivering GenAI systems in an enterprise environment (building services/APIs, integrations, tests, and telemetry).
Practical experience with LangChain, LangGraph, and LangSmith (tracing, debugging, evaluation, and/or prompt/workflow regression).
Experience working in Agile delivery environments (e.g., Scrum/Kanban), collaborating effectively with cross-functional teams through iterative development.

Benefits

Applicant Tracking System Keywords

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

Hard Skills & Tools

PythonGenerative AIservicesAPIsintegrationstestingtelemetryLangChainLangGraphLangSmith

Soft Skills

collaborationiterative developmentstakeholder engagementproblem-solvingcommunication