Senior LLMOps Engineer - Scalable GenAI Platform Lead

UNAVAILABLE; McLean (VA); On-site; USD 180,000 - 240,000; Full time

Job summary

UNAVAILABLE is seeking an experienced Senior LLMOps Engineer to design and maintain production-grade LLM pipelines, deployment architectures, and monitoring across enterprise environments. This role spans model deployment, evaluation, optimization, and RAG pipelines.

You will lead secure GenAI infrastructure, implement CI/CD for AI workloads, integrate vector databases, and ensure governance, privacy, and cost efficiency while mentoring junior engineers.

Qualifications

• Ability to obtain and maintain a U.S. government security clearance.
• Bachelor’s degree and 10+ years of total experience.
• 5+ years in software engineering, data engineering, MLOps, or cloud engineering, with 2+ years in LLM/GenAI operations.
• Hands-on experience building RAG pipelines.
• Fluency in Python.
• Experience deploying models with HF Transformers, vLLM, TensorRT-LLM.
• Experience with FastAPI, PyTorch, LangChain, LlamaIndex, vector DBs (FAISS/Milvus/Pinecone).
• Cloud platforms (AWS/Azure/GCP) with hosting, compute, secure networking.
• CI/CD pipelines, testing for AI workloads.
• Docker, Kubernetes, Terraform/CloudFormation.
• MLSocOps, AI governance, model hardening, content safety monitoring.
• Logging/observability for high-throughput LLMs.
• Excellent written and verbal communication.
• Balance long-term platform thinking with hands-on ops.
• Experience in Agile environments.

Responsibilities

• Architect, build, and maintain LLM and RAG pipelines including hosting and retrieval layers.
• Lead secure GenAI infrastructure across cloud environments for reliability and cost efficiency.
• Build automated evaluation systems for LLM output quality, safety, latency, and governance.
• Develop CI/CD workflows for LLM/GenAI apps, including data/versioning and model lineage.
• Collaborate with AI Product Engineers and Data Scientists to productionize prototypes.
• Integrate vector databases, model gateways, content filters, and guardrails.
• Implement observability tracking performance, hallucinations, costs, and user patterns.
• Lead troubleshooting and root-cause analysis for deployment and pipeline issues.
• Develop Python-based services and integrations supporting LLM/RAG pipelines.
• Stay current with MLSecOps patterns and AI governance frameworks.

Skills

Python

Communication

Agile

Education

Bachelor's degree

Tools

Hugging Face Transformers

vLLM

TensorRT-LLM

FastAPI

PyTorch

LangChain

LlamaIndex

FAISS

Milvus

Pinecone

Docker

Kubernetes

Terraform

CloudFormation

AWS

Azure

GCP

Job description

UNAVAILABLE is seeking an experienced Senior LLMOps Engineer to design and maintain production-grade LLM pipelines, deployment architectures, and monitoring across enterprise environments. This role spans model deployment, evaluation, optimization, and RAG pipelines.

You will lead secure GenAI infrastructure, implement CI/CD for AI workloads, integrate vector databases, and ensure governance, privacy, and cost efficiency while mentoring junior engineers.