Senior AI Software Engineer

Credence•McLean, VA

About The Position

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 Senior AI Software Engineer to join our growing AI and Automation practice. In this role, you will serve as a senior technical contributor responsible for designing, developing, and deploying advanced AI-driven solutions, including generative AI, LLM-powered applications, and agentic AI systems. You will collaborate with cross-functional engineering, data, cloud, and stakeholder teams to deliver scalable, secure, and mission-focused AI capabilities for federal clients, while helping guide technical direction, strengthen engineering practices, and mentor other engineers.

Requirements

Bachelor's or Master's in Computer Science, AI/ML, or a related field.
7+ years of hands-on software engineering experience, including significant experience delivering AI/ML, generative AI, or LLM-powered solutions in production or production-like environments.
Experience building generative AI applications, working with LLMs, implementing tool/function calling, and applying model evaluation, prompt/context engineering, or retrieval-augmented generation approaches.
Experience designing or implementing agentic AI solutions using frameworks or platforms such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph.
Strong understanding of leading AI APIs and model platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, and Google Vertex AI.
Proficiency in TypeScript and familiarity with key libraries and frameworks such as Nx, Next.js, Mastra, Vercel AI SDK, Playwright, Jest, and Vite.
Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured).
Demonstrated curiosity and practical experimentation with emerging AI technologies, with a strong focus on responsible innovation and measurable mission impact.
Familiarity with CI/CD pipelines (GitLab CI)
Experience with VS Code and AI extensions such as Cline and Claude Code.
Strong communication skills and client-oriented mindset.
U.S. Citizenship with eligibility for DoD Secret clearance.

Nice To Haves

Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact.
Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem.
Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications.
Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.

Responsibilities

Lead the design, development, prototyping, and refinement of AI-powered capabilities using generative AI, large language models, retrieval patterns, prompt/context engineering, and secure API integrations.
Own end-to-end agentic AI development lifecycles, including model selection, agent design, tool/function calling, orchestration, response synthesis, evaluation, and deployment of reliable AI agents.
Apply strong software engineering principles to design maintainable, testable, and scalable systems; conduct code reviews, establish technical patterns, and leverage AI-assisted development tools responsibly to accelerate delivery.
Partner with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and mission needs into operational AI and automation solutions.
Design and automate deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services to support secure, repeatable, and scalable AI delivery.
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 emerging AI/ML trends, agentic frameworks, model capabilities, and engineering practices while mentoring team members and contributing to reusable standards, documentation, and technical design reviews.