Data Engineer
Core
Build and deploy data-driven solutions, specifically data pipelines for generative AI and LLM usage, within federal AI and Automation practices.
Role type
Mid-Level AI Data Engineer
Builds
Cloud-native AI capabilities, data pipelines, and agentic AI systems for federal missions.
Domain
Federal government, AI/ML, Cloud Infrastructure
Deliverable
production ML models | product features
Required skills
ETL/ELT pipeline design, SQL/NoSQL database management, vector databases and embeddings, generative AI/LLM integration, Infrastructure as Code (IaC), CI/CD pipelines, Python, cloud platform engineering (AWS/Azure/GCP)
Preferred skills
Agentic AI frameworks (CrewAI, LangGraph, Agent2Agent), Python data libraries (Pyspark, Pandas), Terraform/CloudFormation, federal cybersecurity frameworks
Technologies
AWS, Azure, GCP, OpenSearch/Elasticsearch, Kafka, Bedrock, Glue, DataBricks, Snowflake, S3, RDS, EBS, Glacier, FAISS, PGVector, Pinecone, Hugging Face, GitLab, GitHub, Jenkins, VS Code, FastAPI, LangChain, Terraform
Responsibilities
Build and optimize data pipelines for generative AI; manage data lakes and warehouses using medallion architecture; model and query large-scale datasets; collaborate on operational agentic AI systems; automate model deployment workflows; monitor and tune AI system performance; write documented code following federal guidelines.
Seniority
Mid-Level, hands-on IC
