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Strategic Project Lead – Legal

AI Summary
Appen is seeking a legal professional to lead strategic pilots for legal AI training and evaluation. The role takes projects from initial scoping through operationalization, defining legal-quality, feasibility, cost, workflow, and expert requirements. It requires a JD or equivalent legal degree, legal-domain experience, and demonstrated leadership of complex projects or operational initiatives. The lead will work closely with attorneys, researchers, customers, and global delivery teams while addressing confidentiality, privilege, and jurisdictional considerations. Experience with AI/ML, data annotation, legal research, contracts, litigation, or compliance is advantageous.
Remote from
USA
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
6 Dec 2026
Listing views
21
Application actions
1
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Opportunity details

About this role.

Appen’s Strategic Project Management team is central to the company’s growth strategy, partnering with leading AI companies and frontier model developers to deliver the data that makes models work. As Strategic Project Lead – Legal, you will run strategic legal pilots and research projects for legal AI model training and evaluation, from initial scoping through to operationalization. This is a hands-on role bridging customer objectives, legal expertise, and Appen’s global delivery capability.

Your Impact

You will own the success of frontier legal AI pilots, taking emerging use cases to validate projects that meet defined standards for legal quality, feasibility, and cost.

Your judgement will shape how case law, contracts, statutes, regulatory filings, and legal reasoning are used for model training and evaluation, with appropriate consideration for privilege, confidentiality, and jurisdictional requirements.

Across Appen’s global delivery organization, you’ll establish the workflows, expert requirements, quality standards, and operational blueprint needed to move successful pilots into scalable programs.

Success in this role will create legal AI pilots that meet their defined success criteria, trusted partnerships with Researchers and Customers, and proven approaches that can be operationalized across future legal programs.

What You Bring

  • JD or equivalent law degree, with 2+ years in private practice, in-house, legal research, or regulatory and compliance work.
  • 2+ years leading complex projects, operational workflows, or subject-matter initiatives.
  • Strong communication and stakeholder-management skills when working with attorneys, legal experts, researchers, and customers.
  • Comfortable working in a fast-paced environment.

Nice to Have

  • Experience working with AI/ML companies, AI labs, or data annotation and evaluation projects.
  • Experience managing legal, technical, or data-intensive projects.
  • Familiarity with legal research, contract analysis, litigation, regulatory/compliance work, or other complex legal workflows.

Why You’ll Love Working Here

At Appen, we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest quality AI solutions for frontier models.

You’ll work on complex challenges that shape the future of AI across industries and geographies, alongside talented people in a culture that values humility over ego. You’ll have the flexibility to deliver in a way that works for you and your team, supported by tools, resources, and development opportunities to continue to build your capability over time.

About Appen

Appen has been a leader in AI training data for over 30 years. We specialise in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.

Compensation

Additional Information

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe position combines legal judgment, AI data-quality requirements, customer delivery, and scalable operations. Success depends on independently resolving ambiguous legal and operational issues across multiple stakeholder groups.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$145,000
US market range (per year)$120k–$180k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. Estimated US annual base-pay market range for a remote legal AI project lead is $120,000–$180,000, with an estimated midpoint of $145,000 per year; yearly cadence is inferred from the full-time US professional role.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you scope a new legal AI pilot for a customer?

I would first clarify the target use case, intended model behavior, success metrics, jurisdiction, data sources, and delivery constraints. I would then identify legal risks such as privilege, confidentiality, licensing, and accuracy requirements before defining an expert workflow, quality plan, timeline, and cost model.

How do you protect confidential or privileged legal information in an AI data project?

I apply data-minimization and access-control principles, confirm authority to use the material, and establish documented handling procedures. Where appropriate, I would require de-identification, segregated environments, vetted experts, audit trails, and escalation paths for uncertain materials.

Describe how you would turn a successful pilot into a scalable program.

I would document the pilot's operating model, task definitions, acceptance criteria, staffing profile, quality thresholds, tooling needs, and exception handling. I would use pilot metrics to refine the workflow, train delivery teams, and establish governance for consistent performance at scale.

How would you resolve disagreement between a legal expert and a customer about acceptable output quality?

I would make the disagreement concrete by mapping it to agreed requirements, examples, and measurable evaluation criteria. I would facilitate a decision that balances legal defensibility, model usefulness, timeline, and cost, while documenting any accepted risks and final standards.

What metrics would you use to evaluate a legal AI data pilot?

I would track legal-expert agreement, annotation accuracy, completeness, turnaround time, rework rate, exception frequency, cost per accepted item, and adherence to confidentiality requirements. The final metric set would be tailored to the customer's specific model-training or evaluation objective.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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