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Peraton

Runs and secures technology for federal agencies

Large Language Model Specialist

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeUnited StatesIn-person

About the Job

Requirements

  • A minimum of 8 years of experience with a bachelor's degree, 6 years with a master's degree, or 3 years with a PhD.
  • Deep expertise in large language model architectures, transformer models, and modern generative AI techniques.
  • Demonstrated experience leading fine-tuning efforts, parameter-efficient training, and advanced prompt engineering.
  • Ability to design and implement end-to-end retrieval-augmented generation pipelines, including embedding workflows, retrieval optimization, and vector database integrations.
  • Hands-on experience with one or more large language model frameworks or orchestration toolchains, such as LangChain or LlamaIndex.
  • Strong Python development skills and experience with distributed compute or GPU-accelerated training environments.
  • Experience architecting and deploying AI/ML or large language model workflows within cloud platforms such as Azure, AWS, or GCP.
  • Understanding of MLOps/LLMOps practices, including versioning, continuous integration/continuous delivery, automated testing, monitoring, and model governance.
  • Ability to lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences.
  • Must be a U.S. citizen and able to obtain or maintain a Public Trust clearance.

Responsibilities

  • Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem.
  • Own architecture and strategy for fine-tuning, retrieval-augmented generation, agentic frameworks, and domain-specific model adaptation.
  • Guide development of high-impact prototypes and oversee the evolution of scalable large-language-model pipelines.
  • Ensure robust governance, security, and performance across model implementations.
  • Partner with engineering, product, and data teams.
  • Provide technical leadership, evaluate emerging large-language-model technologies, set best practices, and drive transformation through the practical, safe, and effective deployment of generative AI.

Desired Qualifications

  • Experience implementing multi-agent or agentic AI systems for task automation and reasoning.
  • Familiarity with large-language-model evaluation frameworks, structured benchmarking, or human-in-the-loop refinement methods, such as RLHF-style workflows.
  • Expertise with advanced retrieval techniques such as hybrid search, graph retrieval, or long-context optimization.
  • Experience optimizing model inference through quantization, model compression, or model distillation.
  • Background integrating large-language-model services with large-scale analytics environments such as Databricks, Snowflake, or Spark.
  • Strong skills in exploratory data analysis, feature engineering, and data modeling to support domain-specific large-language-model customization.
  • Experience developing innovative prototypes or proof-of-concepts that leverage state-of-the-art generative AI approaches.
  • Exposure to emerging architectures such as mixture-of-experts models, long-context transformers, or experimental generative frameworks.

About the Company

Peraton

Runs and secures technology for federal agencies

Peraton builds and runs secure technology for American defense, intelligence, space, and civilian agencies, from military networks to satellite ground stations. In 2025, the Federal Aviation Administration chose it to manage the overhaul of the nation's air traffic control system, replacing copper wiring with fiber and upgrading radar and radios. Its engineers, many holding security clearances, run and defend agency networks and data centers, write mission software, and operate space and communications systems, and agencies pay for this work through multiyear contracts. Peraton was formed in 2017, when private-equity firm Veritas Capital bought Harris Corporation's government IT business, and is based in Reston, Virginia.

Company size
10,001+
Company stage
Grant
Total funding
$60M
Headquarters
Reston, VA
Founded
2017

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