Data Engineer
Listed on 2026-08-06
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Software Development
AI Engineer (Applied/Software), Data Engineering
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.
PositionSummary
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.
Responsibilitiesinclude, but are not limited to the duties listed below
- 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 Cline and Claude Code.
- Strong communication skills and client-oriented mindset.
- Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of 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…
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