Systems Engineering, Advisor

Peraton; Herndon (VA); On-site; USD 104,000 - 166,000; Full time

Job summary

Peraton seeks an LLM Specialist to design, develop, and operationalize cutting-edge generative AI capabilities across a cloud-based analytics ecosystem. You will own architecture for finetuning, RAG, and domain-specific model adaptation, guiding high-impact prototypes and scalable pipelines.

You will partner with engineering, product, and data teams to drive governance, security, and performance, while advancing practical, safe deployment of AI.

Qualifications

• Deep expertise in LLM architectures and generative AI techniques.
• Experience leading finetuning, parameter-efficient training, and advanced prompt engineering.
• End-to-end RAG pipelines with embedding workflows, retrieval optimization, and vector DB integrations.
• Hands-on with LLM frameworks/orchestration tools like LangChain or LlamaIndex.
• Strong Python development and distributed/GPU training experience.
• Experience deploying AI/ML workflows on Azure AWS or GCP.
• Knowledge of MLOps/LLMOps including versioning, CI/CD, testing, monitoring, governance.
• Ability to mentor teams and explain AI concepts to non-technical audiences.
• Ability to obtain/maintain a Public Trust clearance.

Responsibilities

• Design, develop, and operationalize advanced LLM capabilities across a cloud analytics ecosystem.
• Lead architecture and strategy for finetuning, RAG, agentic frameworks, and domain-specific adaptation.
• Guide prototypes, evolve scalable LLM pipelines, ensure governance, security, and performance across models.

Skills

LLM architectures

Finetuning

RAG pipelines

LangChain/LlamaIndex

Python

Cloud platforms (Azure AWS GCP)

MLOps/LLMOps

Technical leadership

Public Trust clearance

Multiagent/agentic AI

RLHF style workflows

Retrieval techniques

Model optimization (quantization)

Databricks/Snowflake/Spark

Data modeling

Prototyping/POCs

Mixture-of-experts architectures

Education

BS/BA

MS/MA

PhD

Tools

LangChain

LlamaIndex

Job description

Responsibilities

The LLM Specialist will drive the design, development, and operationalization of advanced largelanguagemodel capabilities across a cloudbased analytics ecosystem. This role leads innovation efforts around cuttingedge AI, owning the architecture and strategy for finetuning, retrievalaugmented generation (RAG), agentic frameworks, and domainspecific model adaptation. The specialist will guide the development of highimpact prototypes, oversee the evolution of scalable LLM pipelines, and ensure robust governance, security, and performance across all model implementations. Partnering with engineering, product, and data teams, this position provides technical leadership, evaluates emerging LLM technologies, sets best practices, and helps drive transformation through the practical, safe, and effective deployment of generative AI.

Qualifications

Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD

Required Skills

• Deep expertise in LLM architectures, transformer models, and modern generative AI techniques.


• Demonstrated experience leading finetuning efforts, parameterefficient training, and advanced prompt engineering.


• Proven ability to design and implement endtoend RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations.


• Handson experience with one or more LLM frameworks or orchestration toolchains (such as LangChain, LlamaIndex).


• Strong Python development skills and experience with distributed compute or GPUaccelerated training environments.


• Experience architecting and deploying AI/ML or LLM workflows within cloud platforms such as Azure, AWS, or GCP.


• Solid 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.


• Ability to obtain/maintain a Public Trust clearance

Preferred Skills

• Experience implementing multiagent or agentic AI systems for task automation and reasoning.


• Familiarity with LLM evaluation frameworks, structured benchmarking, or humanintheloop refinement methods (e.g., RLHFstyle workflows).


• Expertise with advanced retrieval techniques such as hybrid search, graph retrieval, or longcontext optimization.


• Experience optimizing model inference through quantization, model compression, or model distillation.


• Background integrating LLM services with largescale analytics environments (e.g., Databricks, Snowflake, Spark).


• Strong skills in exploratory data analysis, feature engineering, and data modeling to support domainspecific LLM customization.


• Experience developing innovative prototypes or POCs that leverage stateoftheart generative AI approaches.


• Exposure to emerging architectures such as mixtureofexperts models, longcontext transformers, or experimental generative frameworks.

Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.

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.

EEO

EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.