AI Software Engineer

Credence•Warner Robins, GA

1d•$120,000 - $150,000

About The Position

Credence is hiring an AI Software Engineer for its growing AI and Automation practice. The role contributes to the design, development, deployment, and operation of cloud-native AI capabilities supporting federal missions. Under mentorship from senior AI leaders, the engineer helps drive agentic AI development lifecycles and collaborates with engineering, data, and stakeholder teams. The work includes prototyping and refining generative AI and LLM capabilities; supporting agent systems from model selection through response synthesis and background operation; applying strong software engineering practices and AI code-generation tools; automating deployment workflows; monitoring and optimizing production systems; and producing clean, documented, reproducible code in accordance with industry and federal guidelines. The position emphasizes mentorship, technical design reviews, professional growth, and delivering mission impact for defense and health agencies.

Requirements

Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field.
3–7 years of hands-on experience delivering AI/ML solutions.
Experience with generative AI, LLMs, and adding tool calls (MCP).
Experience with agentic frameworks such as Agent2Agent Protocol, Mastra, Strands, AgentCore, and/or Gemini Agent Platform.
Deep understanding of AI APIs such as OpenAI, Anthropic, Gemini, and Bedrock.
TypeScript proficiency and familiarity with libraries and frameworks including Nx, NextJS, Mastra, Vercel AI SDK, Playwright, Jest, and Vite.
Python proficiency and familiarity with libraries and frameworks including uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, and Unstructured.
Experience deploying applications using cloud platforms such as AWS or GCP and container tools such as Docker or Kubernetes.
Familiarity with CI/CD pipelines, including GitLab CI.
Experience with AI coding tools such as Claude Code, Codex, or Antigravity.
Strong communication skills and a client-oriented mindset.
U.S. citizenship and eligibility for a DoD Secret clearance.

Nice To Haves

Curiosity and experimentation with the latest AI innovations, with an orientation toward delivering mission impact.
Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering.
Experience with Infrastructure as Code 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

Contribute to projects using generative AI and LLMs by prototyping, customizing, and refining AI-powered capabilities.
Support end-to-end AI development, including model selection, agent creation, tool calling, response synthesis, and ambient background agents.
Apply software engineering principles and AI code-generation tools to development workflows.
Collaborate with data engineers, software engineers, and data scientists to develop operational agent AI systems.
Help automate model deployment workflows using Infrastructure as Code, CI/CD pipelines, and container orchestration tools.
Monitor deployed AI systems, tune performance, and apply reliability and scalability best practices.
Write clean, well-documented code in accordance with industry and federal guidelines and support reproducible development.
Stay current on AI/ML trends and tools and learn from senior team members through mentorship and technical design reviews.