{"id":1510481,"url":"https://alion.io/job/thomson-reuters-lead-ai-forward-engineer-6","title":"Lead AI Forward Engineer","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":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Eagan, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":127400,"max":236600,"currency":"USD","period":"year","gross":null,"usd_annual":236600},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"ITSM","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"ServiceNow","optional":true}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-27T00:08:53Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":28},"description":"Job Description\nThe Lead AI Forward Engineer designs and guides the delivery of AI-powered solutions that reduce operational toil and accelerate technology teams across the CIO organization. This role operates as a forward-deployed solution architect and engineer, partnering closely with teams to identify opportunities, design end-to-end architectures, and drive implementations to production.\nYou will own solution design from concept through deployment, ensuring solutions are scalable, maintainable, extensible, secure, and operationally reliable. You will evaluate emerging AI technologies, define repeatable patterns, and help build new capabilities through hands-on implementation, mentorship, and shared standards.\nKey Responsibilities\nIdentify high-impact opportunities to apply AI automation and intelligent agents across CIO technology teams.\nPartner with engineering teams, service owners, and stakeholders to translate business needs into technical requirements, solution designs, and delivery plans.\nDesign end-to-end AI solutions, including workflows, integration patterns, data flows, APIs, and operational considerations.\nGuide implementations from prototype through production, ensuring solutions meet reliability, security, compliance, and maintainability expectations.\nDefine reusable architectural patterns and reference designs to enable broader adoption of AI capabilities across teams.\nBuild scalable pipelines to collect and analyze inference-level and workflow-level telemetry, integrating data with Thomson Reuters' data backbone.\nDevelop dashboards and reporting that provide visibility into AI performance, reliability, safety, usage, and cost.\nEnsure compliance with Thomson Reuters AI standards for monitoring, governance, privacy, auditability, and operational controls.\nEvaluate and recommend AI/ML technologies and platforms-including LLM orchestration, agentic frameworks, cloud AI services, and observability tooling-based on capability, cost, risk, and enterprise fit.\nDesign flexible architectures that can adapt to changing models, providers, technical requirements, and emerging AI capabilities.\nApply sound judgment on when AI is appropriate and when simpler automation or traditional engineering approaches are better suited to the problem.\nEstablish and track SLIs and SLOs for critical AI services to meet enterprise reliability, performance, and compliance requirements.\nIntegrate AI observability tooling into CI/CD processes so new models, prompts, workflows, and use cases are automatically enrolled in monitoring and evaluation.\nDevelop automated guardrails and policy-enforcement mechanisms, such as limits, anomaly detection, and abuse or failure-pattern detection, in partnership with cloud engineering and security teams.\nPartner with Product, Data Science, AI Inference Engineering, and Enterprise AI teams to design and operate evaluation frameworks for LLM and ML systems, including offline and online tests, benchmarks, canaries, and A/B experiments.\nWork with Product, Data Science, AI Inference Engineering, and Enterprise AI teams to onboard AI use cases into the observability platform from day one.\nCollaborate with Cloud Engineers across AWS, Azure, and GCP, along with SRE and platform teams, to align AI observability with broader platform observability, capacity planning, and operational management.\nSupport the scaling, monitoring, and operational readiness of AI infrastructure and workloads during major releases and global events.\nCommunicate technical trade-offs, architecture decisions, risks, and recommendations clearly to technical and non-technical stakeholders, including senior leadership.\nMentor engineers and share patterns, practices, and lessons learned to raise overall AI solution design and delivery maturity.\nRequired Qualifications\n6+ years of progressive experience in solution architecture, technical strategy, senior engineering, platform engineering, or related technical roles.\nExperience building software prototypes and delivering solutions to production in ambiguous, low-precedent environments.\nStrong end-to-end solution design and architecture capability, including integration patterns, APIs, data flows, distributed systems, and operational design.\nWorking knowledge of AI/ML and LLM application patterns, including LLM capabilities and limitations, prompt design, orchestration approaches, agent workflows, RAG, vector search, and enterprise integration considerations.\nPractical understanding of production AI system trade-offs, including latency, quality, cost, safety, reliability, context-window constraints, hallucinations, and provider variability.\nExperience designing, building, operating, or observing production AI systems and associated telemetry, monitoring, evaluation, and operational workflows.\nProficiency in Python, with the ability to prototype, validate, and support solution designs through hands-on technical work.\nCloud architecture familiarity in AWS, Azure, or GCP, including common service patterns, enterprise constraints, and security considerations.\nKnowledge of microservices, distributed systems, CI/CD, cloud-native architectures, and API-driven integration approaches.\nExperience with DevOps, Platform Engineering, or SRE principles and designing systems for operational excellence.\nStrong communication skills, with the ability to document designs, influence decisions, and align diverse technical and business stakeholders.\nDemonstrated technical leadership through mentoring, architectural governance, cross-team enablement, or shared standards.\nPreferred Qualifications\nFamiliarity with LLM frameworks and patterns, such as LangChain, LlamaIndex, or comparable technologies.\nExperience with AI observability, including telemetry pipelines, dashboards, alerting, service-level indicators, service-level objectives, and evaluation frameworks.\nExperience designing AI guardrails, policy enforcement, anomaly detection, or AI safety and reliability controls.\nExposure to enterprise service management platforms, such as ServiceNow or comparable ITSM tools.\nExposure to security architecture, privacy, compliance-oriented environments, enterprise governance, and auditability requirements.\nExperience collaborating with Product, Data Science, AI Inference Engineering, Enterprise AI, Cloud Engineering, SRE, or Platform Engineering teams.\nExperience supporting the scaling and monitoring of AI infrastructure and workloads in large, complex enterprise environments.\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.\nIn 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 with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan.Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations.\n\nFor any eligible US locations, unless otherwise noted, the base compensation range for this role is $127,400 USD - $236,600 USD.\n\nBase pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.\nThis role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.\n\nAbout Us\nThomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.\nWe are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.\nAs a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. 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