{"id":2899043,"url":"https://alion.io/job/thomson-reuters-director-engineering-ai","title":"Director, Engineering, AI","company":{"id":1951,"name":"Thomson Reuters","domain":"thomsonreuters.com","url":"https://alion.io/company/thomson-reuters","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":87,"open_postings":97,"ghost_share":0.041,"stale_share":0.33,"repost_share":0.134,"time_to_fill_p50_days":24,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Frisco, United States","Toronto, Canada","United States"],"countries":["US","CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":158900,"max":295100,"currency":"USD","period":"year","gross":null,"usd_annual":295100},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"RAG","optional":false},{"name":"AI Agents","optional":true},{"name":"Anthropic","optional":true},{"name":"FinOps","optional":true},{"name":"OpenAI","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-10-19T00:00:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-25T12:51:46Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Director, Engineering, AI\nJob Description\nAre you passionate about transforming how legal professionals find trusted answers with AI? Join our Global Westlaw Engineering organization and help shape the future of AI-driven legal research.\nWestlaw helps legal professionals around the world research, analyze, and act with confidence. We are building the next generation of fiduciary-level, AI-powered legal research and workflow capabilities, and we are changing how we build software.\nAs Director, you will lead a global organization of engineering managers, senior engineers, and vendor partners. You will own the multi-year AI engineering strategy and its alignment with the product delivery roadmap. You will move the organization to mission-based teams with clear ownership and accountability. You will also drive the shift to AI-assisted, agent-driven development and use engineering data to guide decisions and show results.\nWe want a technical leader with a track record of leading AI transformation, who leads by example, stays hands-on, keeps up with AI and engineering best practices, uses data to find what needs to change, and empowers teams to innovate across the organization.\nKey Responsibilities:\nLead\nLead a high-performing global organization. Set clear expectations, coach managers and engineers, and lead by example, using AI tools and engineering data in your own work.\nStay close to the technical work. Work directly with senior engineers on architecture, technical direction, and hard problems to raise the technical bar across the organization.\nOwn Engineering strategy implementation and its alignment with the product delivery roadmap. Run it as a living plan with clear milestones and owners, adapt quickly as priorities evolve, and recommend measures that keep engineering objectives aligned to business strategy.\nLead the transformation to a mission-based operating model. Replace project-by-project handoffs with long-lived teams that own a product area, service, or customer outcome from design through production support. Define each team's mission, scope, decision rights, and the skills and authority it needs.\nSet measures for each mission. Define measures such as reliability, quality, delivery speed, adoption, and cost. Review them regularly and use them to guide priorities, resourcing, and accountability.\nManage the vendor relationship. Help the vendor keep pace with business needs. Integrate vendor-managed teams into the organization, with clear scope, outcomes, service levels, and governance. Hold them to the same standards as internal teams for architecture, quality, security, and delivery, and measure their performance with the same data. Make sure they document their work and transfer knowledge, so the organization does not depend on a single vendor.\nDecide what to do in-house, with partners, or through vendors. Balance cost, speed, capability, risk, and long-term knowledge retention.\nCommunicate proactively. Show how your organization's work delivers business value and supports strategy, and work directly with stakeholders and peers to shape the future of our products.\nDeliver\nDeliver strategic projects with urgency. Partner with Product Management, UX Design, and other Technology teams. Remove blockers, make timely decisions, and enable your teams to solve complex business problems with clearly defined outcomes.\nDrive the end-to-end AI lifecycle. Own the work from retrieval and model integration through evaluation, deployment, and monitoring.\nSet the standard for operational excellence. Hold AI and non-AI services to high standards for reliability, security, performance, and cost. Champion a DevOps-first model supported by automation, CI/CD, and infrastructure as code on AWS.\nManage the project portfolio. Own budget, priorities, and staff allocation.\nOperate: Run a Data-Driven, AI-Enabled Organization:\nProvide guardrails and empower teams to use AI. Equip managers, engineers, and teams to apply AI in daily engineering work, including coding assistants, agents, code review, test automation, and quality evaluation. Provide clear guardrails for responsible use, covering security, data handling, and human review of AI-generated code and outputs. Within those guardrails, encourage teams to experiment and adopt AI, and remove the barriers that slow them down.\nMake decisions with data. Analyze GitHub data, such as pull request cycle time, review latency, build and deployment frequency, and AI tool usage, to find bottlenecks and show where change is working.\nTrack ownership and accountability. Use incident response, change failure rate, and cycle time by team to show whether ownership and accountability are improving. Share results openly, use them to coach rather than blame, and turn them into practical changes in how teams work.\nMeasure the impact of AI. Track its effect on delivery speed, code quality, defect rates, and reliability. Use those measures to adjust strategy and investment.\nOwn the economics of AI usage. Set AI budgets, and track and optimize token consumption, inference cost, and tooling spend. Guide model selection and cost-versus-quality trade-offs, balancing them against productivity, quality, and speed.\nInnovate\nStay on top of the AI landscape. Follow new models, agent frameworks, tool protocols such as MCP, and retrieval patterns. Judge what is production-ready, bring it into your teams' practices, and grow adoption of AI/ML engineering practices and frameworks across the enterprise.\nTry new approaches. Take informed risks. Encourage your managers and teams to do the same, and recognize those who do.\nRequired Qualifications\nEducation. A bachelor's degree in computer science, information technology, or a related field, or equivalent practical experience.\nExperience. 10+ years in software development, including 3+ years leading AI solution development, and 10+ years managing managers and building high-performing engineering teams in an agile environment.\nOrganizational leadership. Experience leading managers, individual contributors, and vendor-managed teams, including scope, performance, cost, and quality. You can coach managers on people leadership and engage credibly with Staff and Principal engineers.\nStrategy and execution. Experience turning a multi-year vision into programs, roadmaps, and measurable results across multiple teams, including large-scale rollouts and infrastructure initiatives.\nShipping AI in production. A track record of shipping LLM-based applications, RAG, or agent workflows in production-grade software. You can speak credibly about prompt and context design, retrieval, evaluation, and production trade-offs.\nCloud, DevOps, and reliability. Strong depth in cloud-native architecture on AWS, CI/CD, and infrastructure as code, and experience running mission-critical, high-availability systems.\nHands-on AI tool use. Daily use of AI coding tools (e.g., GitHub Copilot, Cursor, Claude Code). You lead by example and have empowered managers and teams to adopt AI-assisted development, with strong practices for review, quality, and security.\nData-driven leadership and AI economics. Experience defining and analyzing metrics such as DORA, cycle time, quality, and adoption to find problems and show results. Working knowledge of token usage, inference and tooling costs, and how to measure the return on AI investment.\nLeading change. Experience shifting team mindsets, introducing new tools and ways of working, and moving teams to mission-based, outcome-owned models with clear ownership, decision rights, and accountability.\nCommunication. Excellent communication skills. You can explain complex technical and financial trade-offs to executives and customers and align stakeholders.\nPreferred Qualifications\nExperience leading globally distributed teams and restructuring an engineering organization around products, services, or customer outcomes.\nAgentic systems and responsible AI. Experience shipping agentic systems in production, including evaluation, benchmarking, and monitoring, and knowledge of AI guardrails and governance.\nLLM APIs, search, and agent frameworks. Experience with LLM APIs (e.g., OpenAI, Anthropic) at scale, information retrieval or search systems, and standards such as Model Context Protocol (MCP).\nVendor and cost management. Experience with vendor selection, contract negotiation, and transitions between vendor and in-house teams. Experience managing cloud and AI cost through FinOps or inference cost optimization.\nCareer paths. Experience building career paths for both management and technical (IC) tracks, and retaining senior technical talent.\nTechnical background. Strong Python and RESTful API design skills. AWS certifications, such as Solutions Architect or DevOps Engineer, are a plus.\nDomain background. Background in legal or other regulated, content-rich professional domains.\nThis posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization.\nWhat’s in it For You?\nHybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.\nFlexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.\nCareer Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.\nIndustry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.\n Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.\n Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. \n Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.\nOur use of AI within the recruitment process Thomson Reuters utilizes Artificial Intelligence (AI) to support parts of our global recruitment process. Unless you opt-out, our AI system will assess the information provided by you and compare it to the requirements listed for the role, and present the result to our recruitment personnel for further review. The AI system acts as a supporting tool, but there is always a human making the decision if you will be considered for the role.In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits w...","description_format":"text","description_chars":16033,"description_truncated":true,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Continuous learning","Equity","Flexible schedule","Hybrid work","Life insurance","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["News Agencies","RegTech, AML & Compliance","Accounting & Tax Software","Legal Software"],"lifecycle":[{"event":"open","at":"2026-10-20T05:42:27Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 51 · green card filings: 1","filings_12m":51,"filings_prev_12m":46,"green_card_filings_12m":1,"median_offered_wage_usd":133846,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":2}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":7,"expected_fill_days":24,"reasons":["conf:17","velocity","win:early","comp:brand"],"computed_at":"2026-10-26T05:57:25Z"},"pay":{"stated_usd_annual":295100,"is_top_pay":true},"html_url":"https://alion.io/job/thomson-reuters-director-engineering-ai","json_url":"https://alion.io/job/thomson-reuters-director-engineering-ai.json","meta":{"generated_at":"2026-10-26T18:34:55Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":24865,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-27T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":1951},"rest":"https://alion.io/mcp/rest/get_company?id=1951"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fthomson-reuters-director-engineering-ai"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fthomson-reuters-director-engineering-ai"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fthomson-reuters-director-engineering-ai"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/thomson-reuters-director-engineering-ai\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fthomson-reuters-director-engineering-ai"}]}