Hybrid Staff AI Engineer for Enterprise-Scale RAG

Reuters; Frisco (TX); Hybrid; USD 127,000 - 237,000; Full time

Benefits offered by this job

Hybrid work model

Competitive benefits

Career growth opportunities

Mental health and wellness programs

Job summary

Thomson Reuters in Frisco, TX is seeking a Staff Software Engineer, AI Apply to lead the design and delivery of enterprise-scale AI systems, including multi-component pipelines, RAG architectures and autonomous agents.

You will work with AI researchers and product teams to translate cutting-edge research into market-ready solutions, mentor engineers, and shape technical strategy across cloud-native architectures.

Qualifications

• 8+ years of software engineering experience with 4+ years in senior/lead AI roles.
• Expert-level Python and AI/ML framework experience.
• Deep understanding of ML principles, evaluation, and distributed systems.
• Proven track record delivering enterprise AI systems and MLOps.
• Experience with cloud platforms (AWS, Azure, GCP) and orchestration tools.

Responsibilities

• Design and lead enterprise-scale AI systems and RAG architectures.
• Drive technical strategy and standards across AI initiatives.
• Collaborate with researchers, product, and leadership to turn AI into market-ready solutions.
• Mentor engineers and lead technical discussions in executive forums.

Skills

Generative AI

RAG

LLMs

Python

PyTorch

TensorFlow

JAX

MLOps/LLMOps

AWS

Azure

GCP

Docker

Kubernetes

Terraform

Leadership

Communication

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Docker

Kubernetes

Terraform

PyTorch

TensorFlow

JAX

Job description

Thomson Reuters in Frisco, TX is seeking a Staff Software Engineer, AI Apply to lead the design and delivery of enterprise-scale AI systems, including multi-component pipelines, RAG architectures and autonomous agents.

You will work with AI researchers and product teams to translate cutting-edge research into market-ready solutions, mentor engineers, and shape technical strategy across cloud-native architectures.