Senior AI/ML Software Engineer

Peraton•Woodbridge, NJ

20h•$146,000 - $234,000

About The Position

Peraton Labs is seeking a Senior AI/ML Software Engineer to join the Labs Agentic AI team. In this role, you will design, build, and ship AI-powered systems, focusing 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, all within federal-grade security and accreditation constraints. This position is ideal for someone who thinks deeply about AI agent behavior in high-trust environments, values reliability and auditability, and can work fluidly across distributed orchestration, backend systems, and product-facing features.

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.

Nice To Haves

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.

Responsibilities

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, including REST APIs, streaming interfaces, 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.