Large Language Model Specialist (AWS Cloud)

Peraton; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Peraton seeks an LLM Specialist to drive design, development, and operationalization of advanced large-language-model capabilities within a cloud-based analytics ecosystem.

You will own architecture for fine-tuning, retrieval-augmented generation (RAG), agentic frameworks, and domain-specific model adaptation, guiding prototypes and scalable pipelines while ensuring governance, security, and performance across deployments.

Qualifications

• Deep expertise in LLM architectures, transformer models, and generative AI techniques.
• Experience leading fine-tuning, LoRA/PEFT, and prompt engineering.
• Design and implement end-to-end RAG pipelines with embeddings and vector databases.
• Hands-on with LLM frameworks or orchestration toolchains (LangChain, LlamaIndex).
• Strong Python development and distributed compute or GPU-accelerated training experience.
• Experience deploying AI/ML workflows on cloud platforms such as Azure, AWS, or GCP.
• Solid understanding of MLOps/LLMOps, including CI/CD, automated testing, monitoring, and governance.
• Ability to mentor team members and communicate complex AI concepts clearly.
• US Citizen with the ability to obtain/maintain a Public Trust clearance.

Responsibilities

• Lead design, development, and operationalization of advanced LLM capabilities.
• Own architecture for fine-tuning, retrieval-augmented generation (RAG), agentic frameworks, and domain adaptation.
• Guide high-impact prototypes and scalable LLM pipelines with governance, security, and performance in mind.
• Collaborate with engineering, product, and data teams; evaluate emerging LLM technologies and best practices.

Skills

LLM architectures

transformer models

generative AI techniques

fine-tuning

LoRA/PEFT

prompt engineering

RAG pipelines

embedding workflows

vector databases

LangChain

LlamaIndex

Python development

distributed compute

GPU-accelerated training

cloud platforms

MLOps/LLMOps

CI/CD

model governance

communication of AI concepts

US Citizenship

Education

BS/BA

MS/MA

HS Diploma

PhD

Tools

LangChain

LlamaIndex

Job description

5 years with BS/BA; 3 years with MS/MA; 0 years with PhD, 9 years with a HS Diploma

Mandatory Requirements:

• Deep expertise in LLM architectures, transformer models, and modern generative AI techniques.
• Demonstrated experience leading fine‑tuning efforts, parameter‑efficient training (e.g., LoRA/PEFT), 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.
• US Citizen with the ability to obtain/maintain a Public Trust clearance

Preferred Requirements:

• 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.

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.