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Mid-Level AI Engineer
Mid-Level AI EngineerCredence • McLean, VA, US
Mid-Level AI Engineer

Mid-Level AI Engineer

Credence • McLean, VA, US
3 days ago
Job type
  • Full-time
  • Quick Apply
Job description

Overview

Credence is one of the largest privately held technology services firms in the U.S., consistently recognized as a Top Workplace and featured on the Inc. 5000 Fastest-Growing Private Companies list for 12 consecutive years. We serve the largest defense and health agencies with mission-critical AI / ML, enterprise modernization, and advanced intelligence solutions. Our commitment to servant leadership , innovation , and continuous learning helps our people—and our clients—succeed.

Position Summary

Credence has an immediate need for a Mid-Level AI 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 / ML skills to build and deploy data-driven solutions. Under mentorship from senior AI leaders, you’ll drive model 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

  • AI Model Development & Integration

Support end-to-end AI development : data prep, feature engineering, model training, evaluation, and integration into production pipelines.

  • Collaborative Engineering
  • Work alongside data engineers, software engineers, and data scientists to embed AI into scalable systems and applications.

  • Cloud & MLOps Enablement
  • Help automate model deployment workflows using Infrastructure as Code (IaC), CI / CD pipelines, and container orchestration tools.

  • Generative AI & LLM Usage
  • Contribute to projects using generative AI and LLMs, helping to prototype, customize, and refine models.

  • 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

    What You Bring

  • Bachelor’s or Master’s in Computer Science, AI / ML, Data Science, or a related field.
  • 3–5 years of hands-on experience delivering AI / ML solutions.
  • Familiarity with OpenAI, Claude Sonnet, Claude Opus, and other AI engines.
  • Strong Python proficiency and familiarity with AI / ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Understanding of supervised and unsupervised learning techniques.
  • Experience working with cloud platforms (AWS, Azure, or GCP) and container tools (Docker, Kubernetes).
  • Familiarity with CI / CD pipelines and basic MLOps workflows.
  • Experience or interest in generative AI and working with LLMs.
  • Experience with VS Code and AI extensions like Cline and Claude Code, in addition to QDeveloper.
  • Strong communication skills and client-oriented mindset.
  • U.S. Citizenship with eligibility for DoD Secret clearance.
  • Preferred

  • Experience with Bedrock, Strands, Q Developer, Kiro, AgentCore Gateway.
  • Exposure to AWS Serverless technologies including ones that enable Event based architecture (important for Agentic AI systems).
  • Experience with IaC tools (AWS CDK, Terraform, CloudFormation) or model monitoring tools.
  • Exposure to data engineering concepts or data pipeline optimization.
  • Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.
  • Knowledge of MCP servers and how they can be used for re-usable archetypes between teams.
  • 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, expand into LLM and generative AI, and build expertise in cloud-first MLOps.
  • Culture of Empowerment — You’ll be part of a team that values innovation, trust, collaboration, and mission success.
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