AI/ML Software Engineer

Peraton

$104K — $166K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • BS degree with 5 years, MS degree with 3 years, or PhD with relevant AI/ML experience
  • Hands-on experience in building agentic systems using reasoning and task execution
  • Strong Python skills, including async/await patterns and modern tooling
  • Familiarity with workflow orchestration systems like Airflow or Celery
  • Understanding of agentic frameworks and concepts relevant to AI agent behavior
  • Experience with LLM APIs from providers such as OpenAI or AWS
  • Ability to work across the stack from backend APIs to frontend interfaces
  • Comfort with ambiguity in a dynamic environment

Responsibilities

  • Design and implement AI capabilities using Python frameworks for dynamic workflows
  • Maintain integrations with LLM APIs to facilitate intelligent automations
  • Develop full-stack features that enhance user engagement with AI capabilities
  • Instrument AI agent pipelines with observability tools for performance assessment
  • Write maintainable code adhering to engineering standards in a compliance environment
  • Evaluate and enhance agent performance through debugging and reliability improvements

Benefits

  • Flexible work environment
  • Access to modern tooling and frameworks
  • Opportunities for professional growth in cutting-edge AI technologies
  • Engagement with high-trust federal clients
  • Direct impact on product lifecycle from design to deployment
Full Job Description
Responsibilities

Peraton Labs is seeking an 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 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
Target Salary Range$104,000 - $166,000. 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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