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 of experience, MS with 3 years, or PhD with relevant exposure to AI/ML.
  • Proven experience in building agentic systems utilizing multi-step reasoning and autonomous task execution.
  • Strong proficiency in Python 3.12+; adept with async/await and modern tooling.
  • Experience with distributed execution frameworks like Airflow or Prefect.
  • Familiarity with agentic frameworks and their key concepts.
  • Hands-on experience with LLM APIs such as OpenAI or AWS Bedrock.
  • Comfort across the tech stack including FastAPI/Python backends and React frontends.
  • Must be a US Citizen.

Responsibilities

  • Design and implement agentic AI capabilities using Python frameworks like LangChain.
  • Integrate with various LLM APIs to enable intelligent automations.
  • Develop full-stack features that showcase AI functionalities for end-users.
  • Instrument agent pipelines using OpenTelemetry for enhanced observability.
  • Write maintainable, tested code that adheres to engineering standards in a compliance-focused setting.
  • Evaluate agent performance and continually enhance the reliability of workflows.

Benefits

  • Flexible work environment with opportunities for remote work.
  • Professional development resources and learning opportunities.
  • Access to cutting-edge tools and technologies in AI/ML.
  • Opportunities to work on impactful projects in a federal context.
Full Job Description
Responsibilities

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


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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