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Full Stack Engineer

Job in Richmond, Madison County, Kentucky, 40476, USA
Listing for: Peraton
Full Time position
Listed on 2026-09-02
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Full Stack Developer, DevOps
Salary/Wage Range or Industry Benchmark: 86000 - 138000 USD Yearly USD 86000.00 138000.00 YEAR
Job Description & How to Apply Below

Full Stack Engineer Job Location s

US-OH-Home

Responsibilities

Peraton is seeking a talented and motivated Full Stack Engineer specializing in Agentic AI and External Integrations to join a dynamic team building and operating a cutting-edge Agentic AI platform.

In this role, you will be at the forefront of designing, developing, and maintaining the integrations and intelligent agent capabilities that power a next-generation decision-support platform - spanning delivery, infrastructure, runtime operations, and platform health. You will work across the full stack to connect AI agents with diverse external data sources, package real-world capabilities as reliable agent tools, and ensure that the systems you build are secure, scalable, and production-ready.

If you are passionate about applied AI, thrive in fast-moving environments, and take pride in building platforms that real users depend on, this is an opportunity to make a meaningful impact supporting critical missions.

Location: Columbus, Ohio - candidates must currently reside in the area or be willing to relocate.

Key Responsibilities
  • Design and build integrations to external sources of information, including public APIs, licensed data feeds, partner systems, customer enterprise systems, web content, document repositories, and structured databases
  • Package external capabilities as agent tools and skills with clean interfaces, predictable inputs/outputs, sound error handling, and documentation usable by both AI agents and human configurators
  • Develop and maintain full-stack components spanning FastAPI/Python backends, React frontends, Docker containerization, and PostgreSQL
  • Build and consume web APIs (REST, GraphQL, or comparable), handling production integration concerns such as authentication, pagination, rate limiting, retry/backoff, schema mapping, deduplication, and caching
  • Implement and maintain workflow and task orchestration pipelines using systems such as Airflow, Prefect, Celery, or comparable agent orchestration patterns
  • Integrate LLMs into production or near-production applications, leveraging APIs such as OpenAI, Anthropic, or AWS Bedrock
  • Apply security best practices specific to agentic and external integration work - including secrets management, OAuth and API-key handling, defensive parsing, and prompt-injection awareness
  • Contribute to the build-out and operation of the Agentic AI platform across delivery, infrastructure, runtime operations, and platform health
  • Collaborate across teams with a product mindset, keeping the end-user experience central to technical decisions
  • Collaborates with stakeholders on workflows
Qualifications

Required Qualifications
  • 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 with AI agents - 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
  • Familiarity with agentic frameworks and an understanding of the underlying concepts (chains, tool calling, agent loops) that transfer across tools
  • Comfort operating with some ambiguity in a fast-moving environment
Clearance Requirements
  • US Citizenship is required
  • Ability to obtain a Public Trust
Desired Qualifications
  • Production experience with agent frameworks (Lang Chain, Lang Graph, Llama Index, CrewAI, Auto Gen, OpenAI Agents SDK, Anthropic tool-use, or comparable) and a sound point of view on when each is the right tool
  • Experience designing and operating retrieval-augmented generation (RAG) systems - chunking strategies, embedding models, vector stores, hybrid retrieval, reranking, and grounding/citation patterns
  • Experience integrating with knowledge graphs, document stores, or curated content repositories as agent-accessible sources
  • Experience evaluating agent and LLM systems - building eval harnesses, golden datasets, regression testing, and observability for non-deterministic systems
  • Exposure to orchestration patterns: supervisor agents, parallel tool calls, human-in-the-loop flows, DAG-based pipeline execution
  • Experience building plugin or extension systems: dynamic code loading, container isolation, API mixin patterns
  • Familiarity with prompt engineering, evaluation frameworks, or agent observability
  • Familiarity with federal compliance environments:
    FedRAMP, FIPS 140-2/3, Iron Bank container hardening, OPA policy enforcement, or Section 508 accessibility
  • Experience with observability tooling:
    Open Telemetry, Jaeger, Prometheus, Grafana, or similar distributed tracing/metrics stacks
  • 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 Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest…

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