Description:

Design and implement AI features end to end, from data pipelines through GenAI and agentic workflows to production deployment.
Build and optimize scalable, secure data pipelines and ETL/ELT workflows in Python and SQL across polyglot client enterprise environments.
Develop Generative AI, agentic, ML, and BI systems using modern frameworks (Spark, LangChain, Databricks, etc.).
Implement MLOps/LLMOps practices across AWS, Azure, and GCP.
Enforce data security and governance, including PII/PHI handling and role-based access control.
Mentor junior engineers and champion software engineering best practices.

Requirements:

Active Secret or Top Secret clearance required.
5+ years of relevant professional experience in a data engineering role.
Expert-level proficiency in Python and SQL; familiarity with Scala and Java is a plus.
Strong experience in building Agentic AI, Generative AI, and ML systems using modern frameworks.
Ability to lead AI feature implementation with sound judgment on model behavior and trade-offs.
Experience with data security and governance controls.
Deep knowledge of MLOps/LLMOps, including CI/CD for data workflows and infrastructure as code.
Exceptional time management and ability to own technical workstreams autonomously.

Skills