Director, Engineering, AI

Thomson Reuters•Eagan, MN

3d•Hybrid

About The Position

The Director, Engineering, AI will lead a global engineering organization supporting Westlaw and shape the next generation of AI-powered legal research and workflow capabilities. The role owns a multi-year AI engineering strategy and its alignment with the product delivery roadmap, while moving the organization toward mission-based teams with clear ownership and accountability. The Director is expected to lead by example, remain close to technical work, use AI tools and engineering data, and empower teams to innovate. The Director leads engineering managers, senior engineers, and vendor partners; partners across Product Management, UX Design, and Technology; and owns strategic delivery, portfolio priorities, budget, and staff allocation. The role drives the end-to-end AI lifecycle, from retrieval and model integration through evaluation, deployment, and monitoring, while establishing operational standards for reliability, security, performance, and cost. It also champions DevOps practices, automation, CI/CD, and infrastructure as code on AWS. The role establishes guardrails for responsible AI use and encourages AI-assisted development across coding, agents, code review, testing, and quality evaluation. It uses engineering and delivery data to identify bottlenecks, measure accountability and the impact of AI, and guide investment and organizational change. The Director also tracks AI economics, including budgets, token consumption, inference costs, and tooling spend, and evaluates emerging AI models, agent frameworks, protocols, and retrieval patterns for production readiness.

Requirements

Bachelor's degree in computer science, information technology, or a related field, or equivalent practical experience.
10+ years of software development experience, including 3+ years leading AI solution development.
10+ years managing managers and building high-performing engineering teams in an agile environment.
Experience leading managers, individual contributors, and vendor-managed teams, including management of scope, performance, cost, and quality.
Ability to coach managers on people leadership and engage credibly with Staff and Principal engineers.
Experience translating a multi-year vision into programs, roadmaps, and measurable results across multiple teams, including large-scale rollouts and infrastructure initiatives.
Track record of shipping LLM-based applications, retrieval-augmented generation (RAG), or agent workflows in production-grade software.
Credible knowledge of prompt and context design, retrieval, evaluation, and production trade-offs.
Strong depth in AWS cloud-native architecture, CI/CD, infrastructure as code, and operating mission-critical, high-availability systems.
Daily use of AI coding tools, such as GitHub Copilot, Cursor, or Claude Code, and experience enabling teams to adopt AI-assisted development with strong review, quality, and security practices.
Experience defining and analyzing metrics such as DORA, cycle time, quality, and adoption to identify problems and demonstrate results.
Working knowledge of token usage, inference and tooling costs, and measuring return on AI investment.
Experience leading organizational change, introducing tools and new ways of working, and moving teams to mission-based, outcome-owned models with clear ownership, decision rights, and accountability.
Excellent communication skills, including the ability to explain technical and financial trade-offs to executives and customers and align stakeholders.

Nice To Haves

Experience leading globally distributed teams and restructuring engineering organizations around products, services, or customer outcomes.
Experience shipping production agentic systems, including evaluation, benchmarking, and monitoring, and knowledge of AI guardrails and governance.
Experience with LLM APIs such as OpenAI or Anthropic at scale, information retrieval or search systems, and standards such as Model Context Protocol (MCP).
Experience with vendor selection, contract negotiation, and transitions between vendor and in-house teams.
Experience managing cloud and AI costs through FinOps or inference cost optimization.
Experience building management and individual-contributor career paths and retaining senior technical talent.
Strong Python and RESTful API design skills.
AWS certifications, such as Solutions Architect or DevOps Engineer.
Background in legal or other regulated, content-rich professional domains.

Responsibilities

Lead and develop a high-performing global organization of engineering managers, engineers, and vendor partners.
Set expectations, coach managers and engineers, lead by example with AI tools and engineering data, and stay close to technical work.
Work with senior engineers on architecture, technical direction, and complex technical problems.
Own implementation of engineering strategy and align it with the product delivery roadmap, maintaining milestones, owners, and measures.
Transform teams to a mission-based model with long-lived ownership of product areas, services, or customer outcomes from design through production support.
Define team missions, scopes, decision rights, required skills, and measures; regularly review reliability, quality, delivery speed, adoption, and cost.
Manage vendor relationships and integrate vendor-managed teams with clear scope, outcomes, service levels, governance, documentation, and knowledge transfer.
Decide which capabilities should be delivered in-house, through partners, or through vendors, balancing cost, speed, capability, risk, and knowledge retention.
Communicate organizational results and business value, and collaborate with stakeholders and peers on product direction.
Deliver strategic projects in partnership with Product Management, UX Design, and Technology teams; remove blockers and make timely decisions.
Own the end-to-end AI lifecycle, including retrieval, model integration, evaluation, deployment, and monitoring.
Set operational standards for reliability, security, performance, and cost across AI and non-AI services.
Champion a DevOps-first approach using automation, CI/CD, and infrastructure as code on AWS.
Manage the project portfolio, including budget, priorities, and staff allocation.
Provide responsible-AI guardrails for security, data handling, and human review, while enabling teams to use AI in daily engineering work.
Analyze GitHub and other engineering data, including pull request cycle time, review latency, build and deployment frequency, AI tool usage, incident response, change failure rate, and team cycle time.
Use data to measure ownership, accountability, AI's effect on delivery speed, code quality, defects, and reliability; share results and use them to guide practical changes and investment.
Own the economics of AI usage, including budgets, token consumption, inference costs, tooling spend, model selection, and cost-versus-quality trade-offs.
Monitor AI developments, assess models, agent frameworks, tool protocols, and retrieval patterns for production readiness, and promote AI/ML engineering practices across the enterprise.
Encourage informed experimentation and recognize teams and managers who try new approaches.

Benefits

Comprehensive health, dental, vision, disability, and life insurance.
401(k) plan with company match.
Flexible vacation and sick and safe paid time off.
Paid holidays, including two company-wide mental health days.
Parental leave and sabbatical leave.
Tuition reimbursement.
Employee incentive programs and annual bonus eligibility.
Access to the Headspace app and resources for mental, physical, and financial wellbeing.
Flexible hybrid working environment for office-based roles, with work-from-anywhere options for up to eight weeks per year.
Career development and continuous learning programs, including Grow My Way.
Two paid volunteer days annually and opportunities to participate in pro-bono consulting and ESG initiatives.
Optional hospital, accident, and sickness insurance, paid by the employee.
Optional life and AD&D insurance, paid by the employee.
Flexible Spending and Health Savings Accounts.
Fitness reimbursement and access to an Employee Assistance Program.
Group Legal Identity Theft Protection benefit, paid by the employee.
Access to a 529 Plan and commuter benefits.
Adoption and surrogacy assistance.
Employee Stock Purchase Plan.