AI Software Engineer

Credence•Boston, MA

4d•$120,000 - $150,000

About The Position

Credence is seeking an AI Software Engineer to join its AI and Automation practice. The role applies foundational AI skills to build and deploy data-driven solutions for federal missions. With mentorship from senior AI leaders, the engineer will contribute to agentic AI development lifecycles and collaborate with engineering, data, and stakeholder teams to deliver cloud-native AI capabilities. The work supports defense and health agencies, including missions related to national security and public well-being.

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 and LLMs, including 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 Nx, NextJS, Mastra, Vercel AI SDK, Playwright, Jest, and Vite.
Python proficiency and familiarity with 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 and 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, or platform engineering.
Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation.
Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.

Responsibilities

Contribute to generative AI and LLM projects 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 strong software engineering principles and use AI code-generation tools to accelerate development workflows.
Collaborate with data engineers, software engineers, and data scientists to develop operational agentic 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 that follows industry and federal guidelines and supports reproducible development.
Stay current on AI and machine-learning trends and tools, and learn from senior team members through mentorship and technical design reviews.