Design and maintain scalable data pipelines supporting AI-enabled compliance workflows
Build and optimize Retrieval-Augmented Generation (RAG) pipelines for large-scale document and financial datasets
Engineer ingestion pipelines across structured and unstructured data sources
Integrate relational databases and enterprise data systems into secure, production-grade AI architectures
Collaborate with AI/ML engineers, DevSecOps, cybersecurity specialists, financial SMEs, and UX teams within a regulated DoW environment

Requirements

Active Secret clearance required
Bachelor’s degree in Computer Science, Engineering, or related field
Minimum 5 years of data engineering professional experience
Experience supporting DoD environments preferred
Experience building and maintaining RAG pipelines including document ingestion, chunking, embedding, vector storage, and semantic search
Strong Python proficiency with disciplined typing, functional programming patterns, and async/concurrent execution for data-intensive workloads
Hands-on ETL experience across Excel, XML, YAML, Markdown, and relational databases such as PostgreSQL using SQLAlchemy and schema migrations
Familiarity with LLM integration patterns including prompt engineering, structured response parsing, caching strategies, and evaluation frameworks

Benefits

Applicant Tracking System Keywords

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

Hard Skills & Tools

data engineeringRetrieval-Augmented Generation (RAG)PythonETLSQLPostgreSQLschema migrationsfunctional programmingasync programmingdata pipelines

Soft Skills

collaborationcommunication

Certifications

Active Secret clearance