Staff Software Engineer – AI

Thomson Reuters

. Design and lead enterprise-scale AI systems, including multi-component pipelines, RAG and knowledge graph architectures, and autonomous AI agents with multi-step reasoning .

Posted 10/15/2026full-timeUnited StatesLead💰 $137,100 - $254,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and leading enterprise-scale AI systems, with a strong focus on generative AI, RAG architectures, and MLOps practices. Proven ability to mentor engineering teams, drive technical direction, and ensure compliance with ethical AI principles and regulatory standards.

Highest-signal resume keywords

Enterprise-Scale AI System DesignGenerative AI and RAG ExpertisePython ProficiencyMLOps and LLMOps PracticesTechnical Leadership and Mentoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI/ML Systems DevelopmentBackend Service DesignAPI DesignMachine Learning PrinciplesDistributed SystemsKnowledge GraphsGraph DatabasesVector DatabasesCloud-Native Architectures

Soft Skills

Technical LeadershipMentoringCollaborationCommunication

Tools & Technologies

AWSDockerKubernetesTerraformPyTorchTensorFlow

Industry Keywords

AI GovernanceModel Risk ManagementRegulatory ComplianceLegal Domain ExpertiseLarge-Scale Search Platforms

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerKubernetesMicroservicesPythonPyTorchTensorflowTerraform

About the role

Key responsibilities & impact

Design and lead enterprise-scale AI systems, including multi-component pipelines, RAG and knowledge graph architectures, and autonomous AI agents with multi-step reasoning
Work hands-on across AI orchestration, RAG, API gateways, microservices, and modern web UIs
Evaluate emerging AI techniques and drive adoption
Run proof-of-concept work and assess technical feasibility for AI-driven features
Monitor AI research and translate insights into technical roadmaps
Represent the organization at industry conferences and events
Make architecture decisions and translate business requirements into scalable technical specifications
Mentor senior and junior software engineers
Champion MLOps and LLMOps practices and governance for the AI model lifecycle
Design and implement testing, monitoring, and observability for AI systems at scale
Ensure compliance with ethical AI principles, security standards, and regulatory requirements
Partner with AI researchers, engineering leadership, design, and product to build customer-facing applications
Set technical priorities and remain engaged through delivery
Optimize performance for latency, cost, and user experience
Influence product strategy through technical depth

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or equivalent experience
8+ years of software engineering experience, including 4+ years in senior or lead roles on AI/ML systems
Hands-on experience in generative AI, RAG, or LLM-based systems, covering discovery, architecture, agentic tools, evaluation, deployment, and metrics
Expert-level proficiency in Python or another object-oriented language
Strong backend service and API design skills
Solid understanding of ML principles, evaluation methodologies, and distributed systems
Working experience with AI/ML frameworks such as PyTorch or TensorFlow
Advanced experience with AWS, Docker, Kubernetes, and Terraform
Experience integrating AI models into large-scale production systems through APIs, data pipelines, and cloud-native architectures
Strong technical leadership and mentoring experience as an individual contributor
Experience leading technical direction for agent-based systems or enterprise integrations with AI APIs
Advanced knowledge of vector databases, embeddings, semantic search, and information retrieval
Hands-on experience with knowledge graphs, graph data modeling, ontologies, taxonomies, graph databases, GraphRAG, and entity extraction
Domain expertise in legal, tax, accounting, regulated industries, or large-scale search platforms
Successful AI product launches and experience scaling AI systems to enterprise customers
Experience with AI governance, model risk management, and regulatory compliance
Publications, patents, or speaking experience in AI/ML

Benefits

Comp & perks

Flexible hybrid working environment
Work from anywhere for up to 8 weeks per year
Flexible vacation
Two company-wide Mental Health Days off
Headspace app access
Retirement savings
Tuition reimbursement
Employee incentive programs
Mental, physical, and financial wellbeing resources
Two paid volunteer days off annually
Pro-bono consulting projects and ESG initiatives
Health, dental, vision, disability, and life insurance programs
401(k) plan with company match
Competitive vacation, sick and safe paid time off
Paid holidays, including two company mental health days off
Parental leave
Sabbatical leave
Optional hospital, accident and sickness insurance
Optional life and AD&D insurance
Flexible Spending and Health Savings Accounts
Fitness reimbursement
Employee Assistance Program
Group Legal Identity Theft Protection benefit
529 Plan access
Commuter benefits
Adoption & Surrogacy Assistance
Employee Stock Purchase Plan
Annual Bonus based on enterprise and individual performance