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 data pipeline processes.
Experience with vector databases and generative AI, particularly LLMs.
Familiarity with CI/CD pipelines and tools like GitLab/GitHub/Jenkins.
Strong communication skills and client-oriented mindset.
Responsibilities
Build and optimize data pipelines for generative AI and LLM usage.
Manage and organize large datasets across cloud platforms using data lake and warehouse technologies.
Work with SQL and NoSQL systems to model, query, and load large-scale datasets.
Collaborate with data engineers, software engineers, and data scientists to develop AI systems.
Automate model deployment workflows using Infrastructure as Code and CI/CD pipelines.
Monitor AI systems post-deployment and perform performance tuning.
Write clean, well-documented code following industry and federal guidelines.
Benefits
Health Care Plan (Medical, Dental & Vision)
Retirement Plan (401k, IRA)
Life Insurance (Basic, Voluntary & AD&D)
Paid Time Off (Vacation, Sick & Public Holidays)
Family Leave (Maternity, Paternity)
Short Term & Long Term Disability
Training & Development
Wellness Resources
Full Job Description
Position Summary
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.
Responsibilities include, 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 NoSQL 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.
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.
Preferred
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.
Why This Role Matters
Real-World Impact - Your work will support defense and health agencies where AI solutions directly contribute to national security and public well-being.
Growth-Oriented Environment - Learn from technical leaders, innovate within Agentic AI, and mentor those around you in AI best practices.
Culture of Empowerment - You'll be part of a team that values innovation, trust, collaboration, and mission success.
Salary Range: $115,000 - $155,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications.
