Senior AI Software Engineer (Top Secret Clearance

Senior Software Engineer (AI Systems & Platform)

| U.S. Citizens Only | Top Secret Clearance

We're partnering with an early-stage AI company building mission-critical software for the U.S. Intelligence Community and Department of Defense. Their platform is transforming how sensitive data is securely discovered, shared, and leveraged using modern AI, reducing workflows that once took months down to minutes.

They're looking for a Senior Software Engineer who thrives in high-ownership environments and wants to architect production AI systems that solve real-world national security challenges.

• Own technical direction and architecture for secure, cloud-native AI platforms.
• Design, build, and scale mission-critical backend services and distributed systems.
• Develop AI-powered applications using modern LLM technologies, retrieval pipelines, and agentic workflows.
• Work across software engineering and MLOps to deploy production-ready AI systems.
• Build secure APIs, data pipelines, and cloud infrastructure supporting high-security environments.
• Partner closely with customers and cross-functional teams to translate complex mission requirements into scalable software solutions.
• Help shape engineering standards and leverage AI tooling as part of the daily development workflow.

• 8+ years of software engineering experience with meaningful time at Senior, Staff, or Principal level.
• Strong architecture experience building large-scale, production-grade distributed systems.
• Expert-level Python with FastAPI, Flask, or Django.
• Strong AWS experience and familiarity with cloud-native architectures.
• Experience building secure, reliable services handling large-scale production data.
• Comfortable working with Docker, Kubernetes, CI/CD, and modern Dev Ops practices.

Ideal candidates have hands-on experience building or deploying:

• LLM-powered applications
• Agentic AI systems
• Retrieval-Augmented Generation (RAG)
• Vector search and embeddings
• AI coding tools as part of daily software development
• Production AI infrastructure and inference pipelines

• Vector databases at enterprise scale
• Bedrock, OpenAI, Anthropic, Lang Chain, Lang Graph, MCP, or similar AI frameworks
• Infrastructure as Code and cloud automation
• Dev Sec Ops , SRE, authentication, or encryption
• Government, defense, intelligence, or other highly regulated environments