Staff AI Engineer: Enterprise RAG & Knowledge Graphs

Thomson Reuters Corp.; Minnesota; Hybrid; USD 137,000 - 255,000; Full time

Benefits offered by this job

Hybrid work model

Medical, dental, vision benefits

401k with company match

Tuition reimbursement

Volunteer days

Job summary

Thomson Reuters Corp. in the United States seeks an AI Staff Engineer to define and build AI foundations powering Westlaw experiences. You will work on agentic systems, retrieval-augmented generation, and large-scale knowledge services across Westlaw products.

You will lead architecture, mentor engineers, and drive governance for AI lifecycle while aligning with product strategy and regulatory standards.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience; Master’s preferred.
• 8+ years of software engineering experience with 4+ years in senior/lead AI/ML roles.
• Hands-on AI expertise with generative AI, RAG, LLM-based systems; architecture and deployment experience.
• Proficiency in Python and backend service design; API-driven architectures.

Responsibilities

• Build and architect AI-driven systems including multi-component pipelines and knowledge graphs.
• Drive innovation, evaluate AI techniques, and translate insights into technical roadmaps.
• Provide senior technical leadership, mentor engineers, and govern MLOps/LLMOps practices.
• Ensure quality, security, and observability for scalable AI systems.
• Lead cross-functional collaboration to deliver customer-facing AI applications.

Skills

Python

Backend design

API design

MLOps

LLMOps

AWS

Docker

Kubernetes

TensorFlow

PyTorch

Leadership

Education

Bachelor's in CS

Tools

Neo4j

Terraform

OpenAI API

Anthropic

Job description

Thomson Reuters Corp. in the United States seeks an AI Staff Engineer to define and build AI foundations powering Westlaw experiences. You will work on agentic systems, retrieval-augmented generation, and large-scale knowledge services across Westlaw products.

You will lead architecture, mentor engineers, and drive governance for AI lifecycle while aligning with product strategy and regulatory standards.