New opportunity

Legal AI Solution Consultant

Thomson Reuters · Pyrmont, Australia

About this role

The Legal AI Solution Consultant is a customer-facing pre-sales specialist who helps lawyers assess and adopt Thomson Reuters’ AI-enabled legal technology. Working with Sales, the consultant moves opportunities from discovery through solution design, demonstration, trial and recommendation, connecting product capabilities to customers’ legal workflows and business needs.

Responsibilities

  • Deliver tailored product demonstrations and proof-of-value engagements for AI-enabled legal workflows. Lead discovery, needs analysis, solution design, trials, proposals and recommendations alongside Sales.
  • Assess customers’ priorities, operating models, technology landscapes, data requirements, risk profiles and AI readiness. Translate legal-business challenges into practical solutions using legal technology, AI, automation, content and data capabilities.
  • Bring legal and AI expertise to strategic retention and renewal discussions; identify cross-sell and upsell opportunities across Thomson Reuters’ Legal Solutions portfolio and other products and services.
  • Share customer feedback, recurring challenges, market insights and AI use-case requirements with product, strategy and business teams. Stay informed about legal AI, generative AI, legal operations, data analytics, regulation and competing legal technology.

Required qualifications

6–8+ years of relevant legal and sales experience; experience selling, implementing, supporting or advising on AI solutions in the legal information or technology industry; strong demonstration, presentation, written and verbal communication skills, including engagement with senior contacts; understanding of sales processes and commercial dynamics; ability to prioritize multiple pre-sales projects; cross-sell and upsell skills; and experience with enterprise legal clients or legal operations teams. Preferred qualifications are a strong legal background or legal practice experience, and subject-matter expertise in AI, legal technology and the legal environment.

Working arrangement and benefits: This full-time role is listed in Pyrmont, New South Wales, Australia, as hybrid. Thomson Reuters describes 2–3 office days per week depending on the role and work-from-anywhere flexibility for up to 8 weeks annually. Listed benefits include flexible vacation, two company-wide mental health days, two paid volunteer days, retirement savings, tuition reimbursement and employee incentive programs.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Legal AIGenerative AILegal technologyConsultative sellingPre-salesSolution designProduct demonstrationsProof-of-value engagementsCustomer discoveryNeeds analysisLegal operationsData analyticsClient communicationPresentationEnterprise salesCross-sellingUpsellingStakeholder engagement

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A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Diagnose the legal workflow before proposing a solution

    The role calls for in-depth discovery of customer priorities, legal workflows, operating models, technology, data requirements, risk profiles and AI readiness, then translating findings into practical, scalable solutions.

  • Demonstrate value in the customer’s use case

    Lead tailored product demonstrations and proof-of-value engagements that show AI-enabled legal workflows and connect Thomson Reuters capabilities to the customer’s needs.

  • Move opportunities through pre-sales with Sales

    Partner with Sales across needs analysis, solution design, trials, proposals and recommendations. The posting emphasizes commercial understanding, senior-level communication and managing multiple pre-sales projects.

  • Contribute to retention and portfolio growth

    Bring legal, technology and AI expertise to strategic renewal conversations, and identify relevant cross-sell and upsell opportunities across Legal Solutions and broader offerings.

  • Relay customer insight and stay current

    Share recurring pain points, product feedback and AI use-case requirements with product, strategy and business teams; keep up with legal AI, regulation, legal operations and competing technology.

Likely challenges to think through

  • Show AI value without overlooking adoption risks

    Likely preparation challenge, not a reported employer problem: a persuasive demonstration may not address a customer’s data needs, risk profile or AI readiness. Prepare a discovery-to-proof-of-value approach that makes those constraints visible before recommending a use case.

  • Balance tailored trials against a crowded pre-sales pipeline

    Likely preparation challenge: customer-specific demonstrations and trials take time, while the role requires prioritizing multiple projects and advancing opportunities. Prepare an example of how to scope an evaluation, agree on what it should establish and allocate effort with Sales.

  • Protect advisory credibility while pursuing expansion

    Likely preparation challenge: retention, renewal, cross-sell and upsell goals can pull against a trusted-advisor conversation. Prepare to explain how you would connect any broader recommendation to a demonstrated legal-workflow need rather than a generic portfolio pitch.

03

Practice your answers

Technical practice

How would you structure discovery with an enterprise legal team considering AI?

What to coverThe role calls for discovery of business priorities, legal workflows, operating models and technology landscapes. Preparation suggestion: Explain how you would identify decision-makers, current pain points and a use case worth evaluating before proposing a solution.

How would you assess a customer's data needs, risk profile and AI readiness?

What to coverThe posting names all three as discovery topics. Preparation suggestion: Discuss what information you would request, how you would distinguish an adoption constraint from a solvable design issue, and when you would narrow the proposed use case.

How would you evaluate generative AI output for use in a legal workflow?

What to coverThe role requires legal AI expertise and helping lawyers use AI tools in daily practice. Preparation suggestion: Address accuracy, review by a legal professional and data-handling risks as evaluation considerations, without assuming any particular product feature or control.

How would you turn a legal-business problem into a scalable solution design?

What to coverThe consultant translates customer challenges into solutions using legal technology, AI, automation, content and data capabilities. Preparation suggestion: Walk through how you would map workflow steps to relevant capabilities and explain trade-offs between value, complexity and customer constraints.

How would you tailor a legal AI product demonstration to a customer's use case?

What to coverTailored demonstrations that connect capabilities to customer workflows are a stated responsibility. Preparation suggestion: Describe how you would select a representative scenario, show the workflow rather than a feature list, and handle questions without overstating capabilities.

How would you design and evaluate a proof-of-value engagement?

What to coverThe posting explicitly calls for proof-of-value engagements and trials. Preparation suggestion: Explain how you would agree on a bounded use case, evaluation criteria and evidence of business value with the customer before making a recommendation.

What would you do if a trial did not demonstrate the expected value?

What to coverLeading trials and recommendations is part of the advertised pre-sales lifecycle. Preparation suggestion: Distinguish a workflow mismatch, data limitation or adoption issue from a product limitation, then explain how you would test a remedy or recommend against proceeding.

How would you develop a recommendation and proposal after discovery and trial?

What to coverThe role includes solution design, proposals and recommendations alongside Sales. Preparation suggestion: Tie the proposal to the customer's priorities and trial evidence, state assumptions and trade-offs, and explain the commercial rationale without inventing pricing or terms.

How would you approach a renewal conversation that could reveal an expansion opportunity?

What to coverThe posting calls for domain expertise in retention and renewal discussions and for identifying cross-sell and upsell opportunities. Preparation suggestion: Start with the customer's current value and unmet needs, then explain how you would test whether a broader solution is relevant rather than assume an expansion.

How would you assess a new legal AI development or competing offering?

What to coverThe consultant is expected to stay current on generative AI, legal operations, data analytics, regulation and competing legal technology. Preparation suggestion: Compare implications for customer workflows, risks and demonstrable value, while separating verified product facts from claims that still need validation.

Behavioural practice

Tell me about a time you partnered with Sales on a complex opportunity.

What to coverThe role works closely with Sales across discovery through recommendation. Preparation suggestion: Use a real situation, the actions you took to align responsibilities and advice, and the resulting customer or opportunity outcome.

Describe a time you handled a difficult question from a senior client contact.

What to coverSenior-level client engagement and strong presentation skills are listed requirements. Preparation suggestion: Set out the situation, how you addressed the question without overstating what you knew, and the result for the client's understanding or decision.

Tell me about a time you had to prioritize competing pre-sales commitments.

What to coverThe posting requires managing multiple pre-sales projects simultaneously. Preparation suggestion: Describe the competing demands, your prioritization and communication actions, and what resulted for deadlines and customer needs.

Describe a time you turned customer feedback into a useful internal recommendation.

What to coverSharing recurring pain points and AI use-case requirements with product, strategy and business teams is a stated duty. Preparation suggestion: Give a real example of the feedback, how you established its significance and communicated it, and what happened next.

Tell me about a time you addressed a customer's concern during a renewal or retention discussion.

What to coverThe role supports strategic retention and renewal conversations with legal and AI domain expertise. Preparation suggestion: Explain the customer's concern, your actions to understand and respond to it, and the outcome without implying that every concern led to a renewal.

02

Sharpen your knowledge

Topics to prepare

  • Legal AI in daily practice

    Explain how an AI-enabled legal workflow could help a lawyer, where human review remains important, and what questions you would ask before recommending it. The posting calls for legal-domain and AI expertise that helps lawyers assess and implement AI tools.

  • Enterprise legal workflows and operating models

    Sketch a hypothetical enterprise legal team's workflow, stakeholders and decision points; identify where technology or automation might fit. The role involves discovery with enterprise legal clients and legal operations teams.

  • Data, risk and AI readiness

    For a hypothetical client, list the data requirements, technology constraints, risk concerns and readiness questions you would investigate before solution design. These are explicit areas of customer discovery in the posting.

  • Pre-sales lifecycle and commercial dynamics

    Map discovery, design, demonstration, trial, proposal and recommendation to the decision each stage should support. The role partners with Sales across these stages and requires an understanding of sales processes and commercial dynamics.

  • Legal-technology landscape

    Prepare a short comparison framework covering legal AI, generative AI, legal operations, data analytics, regulation and competing technology; note what you would verify rather than assume about any product. Staying current across these areas is an explicit responsibility.

Skills to revise

  • Run structured customer discovery

    Role-play a meeting with a senior legal contact: ask about priorities, workflows, operating model, technology, data, risk and AI readiness, then summarize the needs back to them. In-depth discovery and senior-level client communication are explicit requirements.

  • Deliver a tailored demonstration

    Rehearse a brief, hypothetical legal-workflow demonstration: state the client's use case, show only capabilities you can substantiate, and connect each step to the stated need. Tailored product demonstrations are central to the role; no specific product feature is assumed here.

  • Plan a proof-of-value trial

    Draft a one-page trial plan with the customer problem, scope, observable success measures, feedback questions and recommendation criteria. The posting calls for proof-of-value engagements, trials and recommendations; the plan is a preparation exercise, not a stated company template.

  • Present a solution recommendation

    Practice a concise proposal that traces a discovered legal-business challenge to relevant legal technology, AI, automation, content or data capabilities, while naming unresolved constraints. The role translates customer challenges into practical, scalable solutions and requires strong presentation and written communication.

  • Handle retention and expansion conversations

    Role-play a renewal discussion: clarify the customer's current value and concerns, then identify a potential cross-sell or upsell only if another need emerges. Strategic retention support and identifying expansion opportunities are explicit responsibilities.

  • Prioritize and relay customer feedback

    Given three hypothetical pre-sales requests, rank them by urgency, customer need and next decision; turn a recurring objection into a concise note for product or strategy teams. The posting requires managing simultaneous pre-sales projects and sharing customer insights internally.

04

Your preparation checklist

  • Draft a customer discovery guide

    The role calls for assessing legal workflows, business priorities, operating models, technology, data, risk and AI readiness. Prepare a one-page question set that would uncover these before proposing a solution.

  • Select a legal AI engagement to walk through

    If you have a relevant example, prepare a concise account of the customer problem, your role, discovery findings, solution choices, demonstration or trial, and outcome. Use only evidence you can substantiate.

  • Sketch a tailored demonstration and proof-of-value

    The posting emphasizes AI-enabled legal workflows. As a practice exercise, choose a hypothetical lawyer use case and outline a demo narrative, trial scope, success measures and how you would handle limitations; do not assume specific Thomson Reuters product capabilities.

  • Practice a solution recommendation

    Turn the hypothetical discovery findings into a short proposal linking legal technology, AI, automation, content or data to the customer's needs. State assumptions, data dependencies, risks and what you would validate with the customer.

  • Prepare evidence of commercial judgment

    Identify examples, where available, of working with Sales, engaging senior enterprise legal or legal-operations contacts, prioritizing concurrent pre-sales work, and recognizing appropriate renewal, cross-sell or upsell opportunities.

  • Form a current-market briefing

    The role requires staying current on legal AI, generative AI, legal operations, data analytics, regulation and competitors. Prepare a brief, qualified view of a few relevant developments and the questions they raise for customer adoption.

  • Write questions for the interviewers

    Ask how Sales and the consultant divide discovery and recommendation work, how proof-of-value success is assessed, and how customer feedback reaches product and strategy teams. These questions probe responsibilities stated in the posting without assuming a particular process.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 1 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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