New opportunity

AI Innovation Advisor

Kirkland & Ellis · Chicago, United States

About this role

The AI Innovation Advisor embeds within Kirkland & Ellis practice groups to turn legal tasks into AI-assisted workflows and support responsible adoption of AI. The role sits on the Innovation Program AI Advisory Services team, works with attorneys, engineers, data scientists and project managers, and reports through matrixed management to the Associate Director of Innovation Engineering. It may support client-facing legal matters as well as internal initiatives.

Responsibilities

Document litigation and transactional workflows, translate attorney needs into scoped requirements, identify opportunities to reuse existing solutions, and advise on AI integration strategy.
Own end-to-end AI legal workflow development: break down tasks, design and test prompts, benchmark outputs against firm standards, and refine workflows with attorney feedback. Maintain decision logs covering requirements, prompt logic, validation criteria, failure modes and platform constraints so workflows can be reconstructed on future infrastructure.
Partner with engineers as workflows mature, coordinate stakeholders and timelines, and maintain client-service quality and confidentiality when supporting client engagements.
Build a scalable playbook of templates, decision trees and implementation guidance. Recommend AI tools and roadmaps; develop attorney demonstrations, guides and feedback mechanisms; report project status, adoption and outcomes; and stay current on AI developments and regulatory changes.

Qualifications

A J.D. from an accredited law school is strongly preferred. Candidates without a law degree who have five or more years leading innovation initiatives, technology adoption or AI implementation at a large law firm or legal technology company will also receive strong consideration.
Requires experience building and refining prompts and workflows on legal AI platforms such as Harvey, Legora, CoCounsel or Lexis+ AI, with accountability for output quality. Candidates should understand generative AI and large language models, legal practice pressures, and billable client-service standards, and bring strong writing, project management, organizational, collaboration and stakeholder-advisory skills.
Preferred: three years as an attorney at an AMLAW 50 firm or comparable legal environment; experience training legal teams or developing governance policies; and knowledge of data security, information governance and compliance.

The posting identifies a hybrid arrangement in Chicago. The Chicago base salary range is $153,000–$191,000; listed benefits include healthcare, paid time off, retirement, and learning and development opportunities.

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

Skills for this role

Generative AILarge Language ModelsPrompt EngineeringAI Workflow DesignAI Workflow TestingOutput BenchmarkingLegal TechnologyHarveyLegoraCoCounselLexis+ AIProcess ImprovementProject ManagementAttorney TrainingResponsible AIInformation GovernanceData SecurityComplianceStakeholder ManagementTechnical Writing

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Scope legal work before building
Embed with litigation and transactional groups, document current workflows, translate attorney tasks into requirements, and identify where existing AI builds can be reused.
Build and validate AI workflows
Own task decomposition, prompt design and testing, output benchmarking against firm standards, and refinement with attorney feedback across legal AI platforms.
Make workflow decisions reproducible
Maintain structured logs of requirements, prompt logic, validation criteria, failure modes, and platform constraints so workflows can be reconstructed on future infrastructure.
Support responsible, client-service delivery
Advise attorneys on AI capabilities, limitations, and governance requirements while maintaining quality and confidentiality when workflows support client matters.
Scale adoption across practice teams
Partner with engineers and other stakeholders, develop playbook materials and attorney training, and report project status, adoption metrics, and outcomes.

Likely challenges to think through

Experimentation versus client-service standards
Preparation hypothesis: rapid prompt iteration may be difficult to reconcile with the quality and confidentiality expected of client work. Prepare to explain how you would define validation criteria, review failures with attorneys, and limit use when outputs do not meet the required standard.
Reuse versus practice-specific needs
Preparation hypothesis: an existing workflow may save effort but miss important litigation or transactional nuances. Prepare a method for documenting the current task, testing a reusable build against it, and deciding when adaptation or a new design is warranted.
Adoption versus competing demands
Preparation hypothesis: attorneys’ pace and multiple concurrent initiatives may make consistent use and feedback hard to sustain. Prepare an approach to focused demonstrations, practical guides, feedback collection, and clear status and outcome reporting across stakeholders.

Practice your answers

Technical practice

How would you map a litigation or transactional task before proposing an AI workflow?

What to coverThe posting calls for documenting current-state workflows and translating attorney needs into scoped requirements. Suggested preparation: explain how you would identify inputs, decisions, outputs, review points and known failure points before defining the scope.

When would you reuse an existing workflow rather than build a new one?

What to coverThe role includes identifying opportunities to leverage existing builds and recommending AI tools. Suggested preparation: compare task fit, output quality, platform constraints and the effort needed to adapt and validate an existing solution.

How would you break down a complex legal task into prompts and review steps?

What to coverThe posting assigns the advisor end-to-end workflow development, including task decomposition and prompt design. Suggested preparation: describe how you would define each step’s purpose, expected output and attorney review point, then refine the prompts through testing.

How would you benchmark an AI-assisted output against firm standards?

What to coverThe posting specifically calls for testing protocols, output benchmarking and attorney-driven refinement. Suggested preparation: define validation criteria for the task, use representative test cases, and explain how attorney feedback would inform revisions.

How would you diagnose a workflow that produces convincing but unreliable results?

What to coverThe role requires understanding where generative AI succeeds and fails and documenting workflow failure modes. Suggested preparation: distinguish problems with the task definition, inputs, prompts and platform constraints, then describe how you would retest a proposed fix.

What would you record so a workflow could be reconstructed on future infrastructure?

What to coverThe posting requires structured decision logs covering requirements, prompt logic, validation criteria, failure modes and platform constraints. Suggested preparation: explain how you would make those records specific enough to reproduce key decisions without relying on undocumented assumptions.

How would you hand a maturing workflow over to engineers?

What to coverThe advisor partners with engineers and bridges attorney domain knowledge with technical execution. Suggested preparation: describe the requirements, test results, unresolved failures and platform constraints you would communicate, along with decisions that still need attorney input.

How would you address confidentiality and responsible AI use in a client-facing workflow?

What to coverThe posting emphasizes client-service quality, confidentiality, firm governance requirements and awareness of data security and information governance. Suggested preparation: explain how you would check applicable requirements, limit use to approved workflows and preserve appropriate human review; do not assume a particular firm policy.

How would you turn a successful workflow into guidance other practice teams can use?

What to coverThe role contributes templates, decision trees and implementation guides to a scalable playbook and helps develop attorney demonstrations and user guides. Suggested preparation: identify what should be reusable, what must remain practice-specific and how you would explain limitations to users.

How would you evaluate whether an AI workflow is being adopted and delivering value?

What to coverThe posting calls for reporting project status, adoption metrics and outcomes to Innovation leadership. Suggested preparation: distinguish usage from useful outcomes, and describe how attorney feedback and output-quality findings would qualify any reported results.

Behavioural practice

Tell me about a time you influenced a senior stakeholder without clear authority.

What to coverThe posting emphasizes credibility with attorneys and leadership in a matrixed, fast-moving environment. Suggested preparation: use a real situation, your actions and the result to show how you understood the stakeholder’s concerns and influenced a decision.

Describe a time you managed competing priorities across several initiatives.

What to coverThe role coordinates stakeholders and timelines while advancing multiple concurrent initiatives. Suggested preparation: give a real situation, the prioritization and communication actions you took, and the resulting delivery or trade-off.

Tell me about a disagreement between subject-matter experts and technical colleagues that you helped resolve.

What to coverThe advisor bridges attorney domain knowledge and engineering execution. Suggested preparation: describe the real disagreement, how you clarified requirements or evidence, and the outcome without overstating your individual contribution.

Describe a time you protected work quality under client-service pressure.

What to coverThe posting highlights pace, quality expectations and confidentiality in work that may support client-facing matters. Suggested preparation: use a real situation, explain the judgment and safeguards you applied, and state the result.

Tell me about a time you helped a team adopt a new tool or workflow.

What to coverThe role includes attorney training, demonstrations, user guides and feedback mechanisms. Suggested preparation: describe the initial concern or obstacle, what you did to support adoption, and what feedback or observable result followed.

Sharpen your knowledge

Topics to prepare

Litigation and transactional workflow design
The posting calls for documenting current-state workflows and identifying reusable solutions or known failure points. To prepare, take a hypothetical legal task in each practice area and outline its inputs, attorney decisions, output, review points and possible AI-assisted steps.
Generative AI capabilities and limitations
The role requires explaining where large language models succeed and fail to attorneys and engineers. To prepare, choose a hypothetical legal-document task and list what an AI output could help draft, what could go wrong, and what an attorney would need to verify.
Output quality and validation principles
The posting specifies firm-standard alignment, output benchmarking and attorney-driven refinement. To prepare, draft validation criteria for a hypothetical legal summary, covering accuracy, completeness and treatment of uncertainty; explain how a failed output would change the workflow.
Responsible AI and client confidentiality
The role includes firm governance requirements and confidentiality in client-facing work; data security, information governance and compliance knowledge are preferred. To prepare, map the approval and handling questions you would raise before using AI on a hypothetical client matter, without assuming a particular firm policy.
Legal AI platform and adoption trade-offs
The posting requires direct experience with Harvey, Legora, CoCounsel, Lexis+ AI or comparable platforms, and calls for tool recommendations and adoption reporting. To prepare, compare platforms you know against one legal workflow's needs, noting constraints, evidence gaps and measures that could show whether attorneys adopt it.

Skills to revise

Capture scoped attorney requirements
The posting calls for translating attorney tasks into scoped requirements. Practice conducting a mock design call, then write a one-page brief stating the task, desired output, quality expectations, stakeholders and opportunities to reuse an existing workflow.
Design and iterate legal-workflow prompts
Hands-on prompt and workflow building is required. Using hypothetical, nonconfidential material, draft a prompt for one legal task, test it on a legal AI platform if available, and revise its instructions based on observed output defects.
Run a repeatable output test
The role owns testing protocols and output benchmarking. Practice scoring several hypothetical outputs against predefined validation criteria, recording failure modes, and specifying the feedback an attorney would need to provide before another iteration.
Maintain a reconstructable decision log
The posting explicitly requires logs detailed enough to rebuild workflows on future infrastructure. Create a sample log covering task requirements, prompt logic, validation criteria, test results, failure modes, platform constraints and reasons for changes.
Explain a workflow and report its progress
The role includes attorney demonstrations, guides, feedback mechanisms, and reporting status, adoption and outcomes. Practice a short demonstration using a hypothetical workflow, then draft a brief status update that separates completed testing, open risks, attorney feedback and proposed adoption measures.

Your preparation checklist

Map a legal workflow
Prepare a sample current-state map of a litigation or transactional task, showing attorney needs, scoped AI requirements, known failure points and opportunities to reuse an existing solution. This reflects the practice-group work described in the posting.
Walk through an AI workflow build
Prepare a sanitized example showing task decomposition, prompt iterations on a legal AI platform, attorney feedback and how outputs were checked against quality standards. Use a hypothetical example if needed; do not expose client material.
Draft a testing and decision log
As a preparation exercise, document validation criteria, benchmark results, failure modes, prompt logic and platform constraints for the example workflow. Be ready to explain how someone could reconstruct it on different infrastructure.
Organize evidence for the stated qualifications
Identify examples, if available, of hands-on legal AI platform work, output-quality accountability, process improvement, writing and concurrent project management. Note that the posting strongly prefers a J.D. and also describes an experience-based route for candidates without one; do not treat preferred experience as required.
Rehearse a stakeholder and client-service scenario
Outline how you would scope an attorney request, coordinate engineers and other stakeholders, and handle quality and confidentiality in a billable, client-facing setting. Present your approach as a proposed method, not a firm procedure.
Prepare an adoption artifact
Sketch one attorney demonstration or user-guide page with a responsible-use limitation, a feedback question and a possible adoption measure. The posting calls for training, governance awareness and reporting outcomes.
Write targeted employer questions
Prepare questions about which practice-group workflows are priorities, how attorney validation and firm governance shape testing, when engineers take over mature workflows, and how adoption and outcomes are measured.

Availability last checked: Nov 4, 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

KEEP EXPLORING

Similar AI jobs

Related skills and specializations in United States. Matched to this role, not your profile.

Explore more jobs

Finding similar opportunities…