Minimum Requirements: • Minimum of a BS degree with 5 years of experience, MS degree with 3 years, or PhD 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 Desired Additional Experience: • Experience with workflow orchestration frameworks for workflow/activity patterns, task queues, worker lifecycle management • Familiarity with federal compliance environments: FedRAMP, FIPS 140-2/3, IronBank 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: OpenTelemetry, 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, JuiceFS) • Prior work building internal tooling, enterprise automation products, or platforms for government customers Peraton Labs is seeking a AI/ML Software Engineer to join the Labs Agentic AI team, you'll design, build, and ship AI-powered systems a compliance-ready, low-code platform for dynamically generating and orchestrating AI agentic workflows. You'll 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 (LangChain, LangGraph, DeepAgents) 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 OpenTelemetry 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