Data Engineer

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Credence has an immediate need for a Mid-Level AI Data Engineer to join our growing AI and Automation practice. You will be a technical anchor in our AI and Automation practice. You ll apply foundational AI skills to build and deploy data-driven solutions. Under mentorship from senior AI leaders, you ll drive agentic AI development life cycles and collaborate across engineering, data, and stakeholder teams to deliver high-impact, cloud-native AI capabilities that advance federal missions.

• Data Integrations for Generative AI & LLM Usage Build and optimize data pipelines that prepare, clean, and structure data for generative AI and LLM usage
• Data Lake & Warehouse Engineering Manage and organize large datasets across cloud platforms (e.g., AWS, Azure, GCP) using data lake and warehouse technologies. Implement medallion architecture (Bronze/Silver/Gold layers) to ensure data quality, lineage, and accessibility
• Database Management & Performance Work with both SQL and No
  
  SQL systems to model, query, and load large-scale datasets. Monitor, tune, and maintain high-performance data stores supporting analytics and reporting
• Collaborative Engineering Work alongside data engineers, software engineers, and data scientists to develop operational agentic AI systems
• Cloud Enablement Help automate model deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, and container orchestration tools
• Production Monitoring & Optimization Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability
• Technical Rigor & Documentation Write clean, well-documented code following industry and federal guidelines, support reproducible development
• Professional Growth Stay current on AI/ML trends and tools and actively learn from senior team members through mentorship and technical design reviews

• U.S. Citizenship with eligibility for DoD Secret clearance
• Bachelor s or Master s in Computer Science, Data/AI/ML, or a related field
• 3-7 years of hands-on experience delivering Data/AI/ML solutions
• Strong understanding of ETL, ELT, and other similar data pipeline processes, as well as Enterprise Data and Storage Systems, such as experience with Open Search/Elastic Search, Kafka, Bedrock, Glue, Data Bricks, Snowflake, AWS S3, RDS, EBS, or Glacier
• Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, Open Search/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base)
• Experience in generative AI, working with LLMs, adding tool calls (MCP) and agents (A2A)
• Understanding of leading AI APIs such as OpenAI, Anthropic, Gemini, Bedrock, Vertex for use with LLMs and RAG search
• Familiarity with CI/CD pipelines (Git Lab/Git Hub/Jenkins)
• Experience with VS Code and AI extensions such as Claude Code
• Strong communication skills and client-oriented mindset

• Curious and experimental about the latest innovations in AI with an orientation toward delivering mission impact
• Python proficiency and familiarity with libraries and frameworks (Pyspark, Pandas, uv, Pydantic, FastAPI, CrewAI, Lang Chain, Lang Graph, Unstructured)
• Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or Cloud Formation to deploy cloud native applications
• Experience with agentic frameworks such as Agent2
  
  Agent Protocol, AWS Bedrock Agents, Mastra, CrewAI, Strands, or…