Large Language Model Specialist

Peraton

. Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem .

Posted 10/13/2026full-timeUnited StatesMid-LevelSenior💰 $104,000 - $166,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates deep expertise in LLM architectures and modern generative AI techniques, with a strong focus on designing and implementing end-to-end RAG pipelines. Proven ability to lead innovation efforts and ensure robust governance and performance across AI model implementations.

Highest-signal resume keywords

LLM ArchitecturesGenerative AI TechniquesEnd-to-End RAG PipelinesPython DevelopmentMLOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM ArchitecturesTransformer ModelsFine-TuningParameter-Efficient TrainingPrompt EngineeringRAG Pipeline DesignEmbedding WorkflowsRetrieval OptimizationVector Database IntegrationsDistributed Compute

Soft Skills

Technical LeadershipMentoringComplex Concept Communication

Tools & Technologies

LangChainLlamaIndexAzureAWSGCP

Certifications & Qualifications

Public Trust Clearance

Industry Keywords

AIMLLLMMLOpsGovernanceSecurityPerformance

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem
Lead innovation efforts around AI, including fine-tuning, retrieval-augmented generation, agentic frameworks, and domain-specific model adaptation
Guide development of high-impact prototypes
Oversee the evolution of scalable LLM pipelines
Ensure robust governance, security, and performance across model implementations
Partner with engineering, product, and data teams
Provide technical leadership and evaluate emerging LLM technologies
Set best practices for generative AI
Drive practical, safe, and effective deployment of generative AI

Requirements

What you’ll need

Minimum of 8 years with BS/BA; minimum of 6 years with MS/MA; minimum of 3 years with PhD
Deep expertise in LLM architectures, transformer models, and modern generative AI techniques
Demonstrated experience leading fine-tuning efforts, parameter-efficient training, and advanced prompt engineering
Proven ability to design and implement end-to-end RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations
Hands-on experience with LLM 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 LLM workflows within Azure, AWS, or GCP
Understanding of MLOps/LLMOps practices, including versioning, CI/CD, automated testing, monitoring, and model governance
Ability to lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences
US citizenship
Ability to obtain and maintain a Public Trust clearance

Benefits

Comp & perks

Potential eligibility for overtime
Potential eligibility for shift differential
Potential eligibility for a discretionary bonus