Senior Data Engineer

Credence•Bath Township, OH

1d•$115,000 - $155,000

About The Position

Credence has an immediate need for a Senior 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 advanced AI and data engineering expertise to design, build, and deploy data-driven solutions. You’ll drive agentic AI development lifecycles and collaborate across engineering, data, and stakeholder teams to deliver high-impact, cloud-native AI capabilities that advance federal missions.

Requirements

U.S. Citizenship with eligibility for DoD Secret clearance.
Bachelor’s or Master’s in Computer Science, Data/AI/ML, or a related field.
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 OpenSearch/Elastic Search, Kafka, Bedrock, Glue, DataBricks, 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, OpenSearch/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 (GitLab/GitHub/Jenkins)
Experience with VS Code and AI extensions such as Cline and Claude Code.
Strong communication skills and client-oriented mindset.

Nice To Haves

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, LangChain, LangGraph, Unstructured).
Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications.
Experience with agentic frameworks such as Agent2Agent Protocol, AWS Bedrock Agents, Mastra, CrewAI, Strands, or AgentCore.
Exposure to adjacent skillsets such as data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem.
Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.

Responsibilities

Build and optimize data pipelines that prepare, clean, and structure data for generative AI and LLM usage.
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.
Work with both SQL and NoSQL systems to model, query, and load large-scale datasets. Monitor, tune, and maintain high-performance data stores supporting analytics and reporting.
Work alongside data engineers, software engineers, and data scientists to develop operational agentic AI systems.
Help automate model deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, and container orchestration tools.
Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability.
Write clean, well-documented code following industry and federal guidelines, support reproducible development.
Stay current on AI/ML trends and tools and actively learn from senior team members through mentorship and technical design reviews.