Mid-Level AI Software Engineer
Listed on 2026-07-01
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Mid-Level Ai Software Engineer
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.
Credence has an immediate need for a Mid-Level AI Software 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.
Responsibilities include, but are not limited to the duties listed below:
Generative AI & LLM Usage
- Contribute to projects using generative AI and LLMs, helping to prototype, customize, and refine AI powered capabilities.
Agentic AI System Development
- Support end-to-end AI development: model selection, agent creation, tool calling, response synthesis, and ambient background agents.
AI Software Engineer
- Maintain strong software engineering principles while leveraging the latest advancements in AI code generation to accelerate your workflows.
Collaborative Engineering
- Work alongside data engineers, software engineers, and data scientists to develop operational agent 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.
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