Lead ML Architect for Production LLM Systems (Hybrid)

LexisNexis; Raleigh (NC); Hybrid; USD 118,300 - 219,800; Full time

Job summary

LexisNexis in Raleigh, NC is seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role owns system architecture, infrastructure, and productionization of ML/LLM solutions, partnering with Data Scientists to turn validated models into reliable, high-performance customer-facing systems.

You will build scalable ML/LLM systems, deploy RAG pipelines and agentic workflows, develop data pipelines, APIs, and model serving,

Qualifications

• Bachelor’s degree in CS, Engineering, or related field.
• Proven experience scaling production ML/LLM systems.
• Experience with LLM apps including RAG and prompt orchestration.
• Experience designing agentic systems and orchestration of multi-step workflows in production.
• Experience with hybrid search, embeddings, and search platforms like Solr/OpenSearch.
• Experience distributed systems and cloud-native development (AWS).
• Experience with streaming and messaging systems (Kafka, SQS) and caching (Redis).
• Proficiency in Python and systems languages (Rust, Go, Scala).
• Experience building scalable APIs (REST/GraphQL).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Strong software engineering fundamentals (system design, testing, CI/CD).

Responsibilities

• Architect and implement scalable ML/LLM systems in production.
• Build and deploy LLM applications, including RAG pipelines and agentic systems.
• Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
• Develop and maintain APIs, microservices, and model serving infrastructure.
• Build data pipelines and streaming systems for large-scale data processing.
• Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
• Optimize systems for latency, scalability, reliability, and cost efficiency.
• Establish best practices for deployment, monitoring, observability, and CI/CD.
• Collaborate with Data Scientists to productionize models and integrate into products.
• Provide technical leadership in system design and engineering standards.

Skills

ML/LLM system design

Python

Systems architecture

Distributed systems

Prompt orchestration

LLM deployment

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Solr

OpenSearch

Kafka

Redis

AWS

DynamoDB

LangChain

LangGraph

AutoGen

Job description

LexisNexis in Raleigh, NC is seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role owns system architecture, infrastructure, and productionization of ML/LLM solutions, partnering with Data Scientists to turn validated models into reliable, high-performance customer-facing systems.

You will build scalable ML/LLM systems, deploy RAG pipelines and agentic workflows, develop data pipelines, APIs, and model serving,