Senior AI​/ML Software Engineer

About Peraton

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace.

The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit  to learn how we're keeping people around the world safe and secure.

Peraton Labs is seeking a Senior AI/ML Software Engineer to join the Labs Agentic AI team. You will design, build, and ship AI-powered systems on a compliance-ready, low-code platform for dynamically generating and orchestrating AI agentic workflows. You will work across the full product lifecycle: from architecting multi-step agentic pipelines backed by Temporal.io, to building the plugin system, APIs, and interfaces that bring them to life, from within federal-grade security and accreditation constraints.

This is a role for someone who thinks deeply about how AI agents should behave in high-trust environments, cares about reliability and auditability, and can move fluidly between distributed orchestration, backend systems, and product-facing features.

Your responsibilities may include:

• Design and implement agentic AI capabilities using Python-based frameworks (Lang Chain, Lang Graph, Deep Agents) and orchestrated workflows
• Build and maintain integrations with LLM APIs (Anthropic/Claude, OpenAI, AWS Bedrock, Ollama) to power intelligent, multi-step automations
• Develop full-stack product features (FastAPI + React) that surface AI capabilities to users - from REST APIs and streaming interfaces to workflow builders and dashboards
• Instrument agent pipelines with Open Telemetry tracing, provenance audit trails, and observability tooling for debugging and performance evaluation
• Write clear, well-tested, maintainable code that passes strict pre-commit validation, and contribute to engineering standards in a compliance-driven environment
• Evaluate agent performance, debug distributed workflows, and continuously improve reliability and output quality

Minimum Requirements:

• Minimum of a BS degree with 12 years of experience, MS degree with 10 years, or PhD with 7 years with meaningful exposure to AI/ML systems or LLM-based products
• Hands-on experience building agentic systems using multi-step reasoning, tool use, RAG pipelines, or autonomous task execution
• Strong Python skills (3.12+); comfort with async/await patterns, type hints, and modern Python tooling
• Experience with workflow or task orchestration systems (Airflow, Prefect, Celery, or similar distributed execution frameworks)
• Familiarity with agentic frameworks and an understanding of the underlying concepts (chains, tool calling, agent loops) that transfer across tools
• Experience working with LLM APIs (OpenAI, Anthropic, AWS Bedrock, or similar)
• Comfort working across the stack:
  FastAPI/Python backends, React frontends, Docker containerization, and PostgreSQL
• A product mindset: you think about the end user, not just the technical implementation
• Comfort operating with some ambiguity in a fast-moving environment
• US Citizenship is a requirement for this position

• Experience with workflow orchestration frameworks for workflow/activity patterns, task queues, worker lifecycle management
• Familiarity with federal compliance environments:
  FedRAMP, FIPS 140-2/3, Iron Bank container hardening, OPA policy enforcement, or Section 508 accessibility
• Experience building plugin or extension systems: dynamic code loading, container isolation, API mixin patterns
• Exposure to orchestration patterns: supervisor agents, parallel tool calls, human-in-the-loop flows, DAG-based pipeline execution
• Experience with observability tooling:
  Open Telemetry, Jaeger, Prometheus, Grafana, or similar distributed tracing/metrics stacks
• Familiarity with prompt engineering, evaluation frameworks, or agent observability
• Experience with container orchestration (Docker SDK, Kubernetes) and distributed storage (S3, MinIO, Juice
  
  FS)
• Prior work building internal tooling, enterprise automation products, or platforms for government customers

Target Salary Range: $146,000 - $234,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift…