Mid-Level AI Engineer

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