Senior AI/ML Software Engineer

Peraton

$146K — $234K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree with 12 years, Master's with 10 years, or PhD with 7 years in AI/ML systems or LLM-based products
  • Hands-on experience with agentic systems using multi-step reasoning and autonomous task execution
  • Strong Python programming skills (3.12+) and familiarity with modern Python tools
  • Experience with task orchestration frameworks like Airflow or Celery
  • Understanding of agentic frameworks and key concepts such as chains and tool calling
  • Experience integrating with LLM APIs like OpenAI and Anthropic
  • Full-stack development experience with FastAPI, React, and Docker

Responsibilities

  • Design and implement AI capabilities using Python frameworks and orchestrated workflows
  • Build and maintain LLM API integrations for multi-step automations
  • Develop full-stack features to present AI capabilities within user interfaces
  • Instrument agent pipelines for tracing and performance evaluation
  • Write maintainable, well-tested code in a compliance-driven environment
  • Debug and evaluate agent performance and improve workflow reliability

Benefits

  • Opportunity to work on cutting-edge AI technologies
  • Engagement in a compliance-driven environment with federal security requirements
  • Collaboration within the Labs Agentic AI team focused on high-trust AI agent behavior
  • Full involvement across product lifecycle from design to deployment
  • Access to a supportive atmosphere for innovation and product thinking
Full Job Description
Responsibilities

Peraton Labs is seeking a Senior 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


Qualifications

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


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


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 differential, and a discretionary bonus in addition to base pay.

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