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Thomson Reuters

Legal, financial data, and media services

Legal Engineer - AI Deployment

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A Juris Doctor from an accredited U.S. law school is required.
  • Prior experience practicing law in a law firm, in-house legal department, government, clerkship, or comparable legal practice setting is required.
  • Proven experience in customer- or client-facing roles, ideally engaging with enterprise or complex accounts.
  • Familiarity with legal workflows and processes such as due diligence, eDiscovery, large document review, compliance, or related domains, gained through direct practice, adjacent roles, or working with legal professionals.
  • Demonstrable experience with generative artificial intelligence applications.
  • Substantial experience using online legal research and practice tools such as Westlaw, Practical Law, HighQ, Relativity, or Everlaw.
  • Demonstrated ability to learn and work hands-on with artificial intelligence tools, workflow technologies, and technically complex solutions.
  • Candidates must be willing and able to travel approximately 25–30%, varying by quarter, to customer and firm sites.
  • Candidates should understand the architecture and operation of large language models and apply that understanding to the hands-on design, testing, and refinement of legal artificial intelligence solutions.
  • Candidates should be comfortable working at the intersection of legal practice and technology, translating ambiguous legal and business needs into structured requirements and testable solutions.
  • Candidates should collaborate effectively with engineering and technical delivery teams, including communicating customer requirements, evaluating solution options, testing outputs, and documenting implementation considerations.
  • Candidates should communicate technical concepts clearly, create high-quality documentation and learning materials, and craft persuasive presentations for non-technical and often skeptical customers, focusing on their needs and outcomes.
  • Candidates should stay up to date with emerging artificial intelligence research and industry trends, and think critically about risks, opportunities, and societal impact.

Responsibilities

  • Lead in-person discovery sessions, solution demonstrations, workflow workshops, and executive briefings with law firm customers to identify priority legal workflows and show how Thomson Reuters Legal AI can address them.
  • Support customers throughout the lifecycle by scoping Legal AI use cases, advising on workflow and solution design, and demonstrating legal AI capabilities.
  • Work with Customer Success, Forward Deployed Engineering, and other cross-functional partners to develop and execute Legal AI strategies for a focused portfolio of signature law firm customers.
  • Partner with Forward Deployed Engineering to translate complex legal workflows and customer requirements into solution designs, prototypes, integrations, or other technically enabled approaches.
  • Design, test, and refine advanced Legal AI workflows, including solutions that may combine Thomson Reuters products, customer systems, partner technologies, integrations, or custom development.
  • Use knowledge of the legal technology ecosystem to determine whether customer needs are best addressed through Thomson Reuters products, a partner solution, an integration, or custom development, and help orchestrate the appropriate approach.
  • Document solution patterns, technical requirements, implementation considerations, and lessons learned so successful approaches can be reused across future customer engagements.
  • Communicate customer needs to Customer Success and cross-functional partners in Product, Engineering, and Marketing, and highlight opportunities to improve and innovate legal AI products.
  • Share expertise with customers and the broader market through events, advisory boards, or customer-facing content.
  • Advocate for Thomson Reuters products by understanding their strengths, areas for improvement, and roadmaps, and explaining how they can be applied to support customers’ client advocacy.

Desired Qualifications

  • Experience with workflow automation, APIs, integrations, technical prototyping, data analysis, Python, or another form of exploratory coding is strongly preferred.
  • Experience collaborating with software engineers, solution engineers, implementation teams, or other technical specialists is preferred.
  • Experience in customer-facing roles, ideally working with enterprise accounts.
  • Experience or demonstrated aptitude in technically oriented areas such as workflow automation, system integrations, APIs, data structures, prompt and context design, technical prototyping, or exploratory coding.
  • Knowledge of due diligence, eDiscovery, managing large document sets, data rooms, and related workflows where artificial intelligence can accelerate results.
  • Ability to work directly with motivated customers to solve complex problems, including through in-person, on-site engagements.
  • Creativity, curiosity, and a growth mindset in problem-solving, with the ability to simplify ambiguous challenges and turn them into opportunities.
  • Willingness to experiment, learn from setbacks, iterate, and improve outcomes.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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