Full Stack SWE getting into AI

Upcoming Tasking

• AI Architecture Best Practices — Produce best-practices documentation and reusable implementation packages that establish repeatable patterns for building and deploying AI enabled software.
• Agentic Coding Harness Testing Framework — Build and maintain the framework that executes repeatable tests against agentic coding harnesses, consuming the datasets and scenarios produced by Fuzzy blocks and running them alongside the Data Scientists' InspectAI benchmarks to measure agent performance and reliability.
• Cross Environment Application Operations — Support deployment, configuration, and operation of applications across both HS and LS environments. This includes ongoing sustainment of deployed applications, implementing small feature requests and enhancements driven by user feedback and evolving mission needs, and diagnosing and resolving bugs across both environments.
• Fuzzy blocks — Build and maintain Fuzzy blocks, a workflow driven framework that generates vulnerability discovery datasets and experimental scenarios fed into the testing harness. It provides a structured approach to creating repeatable benchmark datasets and adversarial test scenarios for AI systems and agents, supporting both research and operational security use cases.

Seven years experience as a SWE, in programs and contracts of similar scope, type, and complexity is required. Bachelor’s degree in Computer Science or related discipline from an accredited college or university is required. Four years of additional SWE experience on projects with similar software processes may be substituted for a bachelor’s degree.

• Python
• FastAPI
• JavaScript / TypeScript
• React
• Docker
• Kubernetes
• Git
• CI/CD tools
• REST APIs
• MongoDB
• Cloud platforms or deployment environments
• Testing frameworks
• Collaboration tools like Jira or Confluence