Lead AI Engineer — RAG & Enterprise AI Systems

Thomson Reuters; Ann Arbor (MI); Hybrid; USD 127,000 - 237,000; Full time

Benefits offered by this job

Hybrid Work Model

Flex My Way

Career Growth

Industry-leading Benefits

Job summary

Thomson Reuters is seeking a Lead Software Engineer, AI to drive AI-driven system design for enterprise-scale platforms. You will lead full-stack development from AI orchestration and RAG through API gateways and microservices, mentoring engineers and shaping technical roadmaps.

The role emphasizes governance of AI model lifecycles, MLOps practices, and collaboration with researchers, product, and design to deliver scalable, secure AI solutions for legal, tax, and compliance domains.

Qualifications

• 8+ years of software engineering experience with at least 4 years in senior or lead roles focused on AI/ML.
• Proven track record with Generative AI, RAG, or LLMs—architecture, agentic tools, deployment, metrics.
• Strong proficiency in backend services and APIs.
• Expert-level proficiency in object-oriented programming and AI/ML frameworks.

Responsibilities

• Lead architecture decisions and translate business requirements into scalable technical specs.
• Mentor senior and junior software engineers; champion MLOps and LLM governance.
• Oversee testing, monitoring, and observability for AI systems at scale; ensure security and regulatory compliance.
• Drive cross-functional collaboration with AI researchers, product, design, and engineering leadership.
• Represent the organization at industry conferences and translate AI insights into roadmaps.

Skills

AI/ML expertise

Backend APIs

Leadership

Cloud orchestration

AWS

Docker

Kubernetes

Terraform

PyTorch

TensorFlow

JAX

Education

Bachelor’s degree in CS/Engineering

Master’s degree preferred

Tools

AWS

Docker

Kubernetes

Terraform

PyTorch

TensorFlow

JAX

Job description

Thomson Reuters is seeking a Lead Software Engineer, AI to drive AI-driven system design for enterprise-scale platforms. You will lead full-stack development from AI orchestration and RAG through API gateways and microservices, mentoring engineers and shaping technical roadmaps.

The role emphasizes governance of AI model lifecycles, MLOps practices, and collaboration with researchers, product, and design to deliver scalable, secure AI solutions for legal, tax, and compliance domains.