External Job Posting Title Systems Engineering, Advisor

Peraton; Idaho; On-site; USD 104,000 - 166,000; Full time

Job summary

Peraton is seeking an LLM Specialist to drive the design, development, and deployment of advanced language models within a cloud analytics environment. You will shape architectures for fine-tuning, RAG, and domain adaptation while leading high‑impact prototypes and scalable pipelines.

You will collaborate with engineering, product, and data teams to establish best practices, governance, and secure, performant model deployments across platforms such as Azure, AWS, and GCP.

Qualifications

• Deep expertise in LLM architectures, transformer models, and modern generative AI techniques.
• Experience leading fine-tuning, parameter-efficient training, and advanced prompt engineering.
• Design and implement end-to-end RAG pipelines, including embedding workflows and vector databases.
• Hands-on experience with LLM frameworks/orchestration toolchains (LangChain, LlamaIndex).
• Strong Python development skills and distributed compute or GPU-accelerated training.
• Experience deploying AI/ML/LLM workflows on Azure/AWS/GCP.
• MLOps/LLMOps practices: versioning, CI/CD, testing, monitoring, governance.
• Ability to mentor, lead technical discussions, and communicate complex AI concepts.
• Ability to obtain/maintain a Public Trust clearance.

Responsibilities

• Drive design, development, and operationalization of LLM capabilities across a cloud analytics ecosystem.
• Lead architecture and strategy for fine-tuning, RAG, agentic frameworks, and domain adaptation.
• Guide prototypes and scalable LLM pipelines; oversee governance, security, and performance.
• Partner with engineering, product, and data teams; set best practices for deployment.
• Evaluate emerging LLM technologies and promote safe, effective production use.

Skills

LLM architectures

transformer models

prompt engineering

Python development

distributed compute

communication

mentoring

public trust clearance

Education

BS/BA (8+ years)

MS/MA (6+ years)

PhD (3+ years)

Tools

LangChain

LlamaIndex

Databricks

Snowflake

Spark

Azure

AWS

GCP

Job description

Responsibilities

The LLM Specialist will drive the design, development, and operationalization of advanced large‑language‑model capabilities across a cloud‑based analytics ecosystem. This role leads innovation efforts around cutting‑edge AI, owning the architecture and strategy for fine‑tuning, retrieval‑augmented generation (RAG), agentic frameworks, and domain‑specific model adaptation. The specialist will guide the development of high‑impact 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 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 one or more LLM frameworks or orchestration toolchains (such as LangChain, 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 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 multi‑agent or agentic AI systems for task automation and reasoning.


• Familiarity with LLM evaluation frameworks, structured benchmarking, or human‑in‑the‑loop refinement methods (e.g., 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 LLM services with large‑scale analytics environments (e.g., Databricks, Snowflake, Spark).


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


• Experience developing innovative prototypes or POCs 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.

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.