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About This Role
Simpson Thacher \& Bartlett LLP is one of the world’s leading international law firms. With offices across the globe, the firm provides coordinated legal advice and transactional capability to a remarkable roster of clients—including many of the world’s largest corporations, financial institutions, and private equity firms. For more than 130 years, Simpson Thacher has built a reputation for superior performance, intellectual rigor, and an unwavering commitment to excellence.
We are committed to leveraging cutting\-edge technology, including artificial intelligence, to enhance our legal services and drive innovation across all practice areas. As part of our ongoing digital transformation strategy, we are seeking exceptional talent to lead our AI initiatives and position the firm at the forefront of legal technology.
The Project Manager will be a strategic leader responsible for creating and driving the project charter, plan, adoption, implementation, and governance of AI technologies across Simpson Thacher \& Bartlett LLP. This role sits at the intersection of technology, legal practice, and program management, requiring an individual who can translate complex AI capabilities into tangible, firm\-wide value. The successful candidate will oversee a portfolio of AI projects, manage cross\-functional teams, and work closely with senior stakeholders to ensure that AI initiatives align with the firm’s strategic objectives and deliver measurable outcomes.
Responsibilities
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- Lead the strategic planning, execution, and delivery of AI programs and initiatives across the firm, ensuring alignment with organizational priorities and business objectives.
- Manage the end\-to\-end lifecycle of AI projects, including requirements gathering, vendor evaluation, implementation, change management, and post\-deployment optimization.
- Oversee the deployment and adoption of AI platforms including Anthropic’s Claude, Harvey (AI for legal professionals), and Microsoft Co\-Pilot across practice groups and business services.
- Report into the Program Management Office (PMO), implementing governance frameworks, reporting structures, and standardized methodologies.
- Apply Agile methodologies (Scrum, Kanban, SAFe) to manage iterative AI development cycles, ensuring rapid delivery of value while maintaining quality standards.
- Serve as the primary liaison between technology teams, legal professionals, firm leadership, and external AI vendors, translating technical capabilities into business language.
- Develop and maintain program roadmaps, budgets, risk registers, and status reports for executive\-level stakeholders and steering committees.
- Contribute to driving organizational change management to foster AI adoption and digital literacy across the firm, including training programs and communication strategies.
- Ensure all AI implementations comply with legal, ethical, and regulatory requirements, including data privacy, confidentiality, and responsible AI principles.
- Manage relationships with key technology partners and outside partners including Anthropic, Harvey AI, and Microsoft, negotiating contracts and ensuring service\-level performance.
- Mentor and coach the PMO team on best practices for running AI programs.
Education
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- Bachelor’s degree
- PMP, Prince2 or CAPM preferred
Skills and Experience
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- 5–10 years of progressive experience in program or project management, with at least 4 years managing AI/ML projects or digital transformation initiatives.
- Proven track record of successfully delivering large\-scale AI programs in complex organizational environments, preferably in professional services or legal.
- Demonstrated experience with Anthropic’s products and platform, including hands\-on familiarity with Claude for enterprise use cases.
- Experience implementing and managing Harvey AI or similar AI platforms purpose\-built for legal professionals.
- Strong expertise in Microsoft Co\-Pilot deployment and integration, including configuration for enterprise\-grade workflows.
- Advanced proficiency in Agile methodologies (Scrum, Kanban, SAFe) with relevant certifications (CSM, PMI\-ACP, or SAFe Agilist).
- Extensive PMO experience, including establishing governance frameworks, portfolio management, resource planning, and executive reporting.
- Exceptional communication skills—both written and verbal—with the ability to present complex technical concepts to non\-technical audiences, including partners and C\-suite executives.
- PMP, PgMP, or equivalent project/program management certification required.
- Strong understanding of AI/ML concepts, natural language processing, large language models, and their practical applications in knowledge\-intensive industries.
- Excellent stakeholder management skills with a track record of building trusted relationships with senior leaders and cross\-functional teams.
- Coaching and mentoring fellow PMO team members.
Preferred
- Experience working in a top\-tier law firm, Big Four consultancy, or large financial institution.
- Familiarity with legal technology ecosystem (document management, e\-discovery, contract lifecycle management).
- Certifications in AI/ML (e.g., Google Cloud AI, AWS Machine Learning, or Microsoft AI certifications).
- Experience with responsible AI governance frameworks and ethical AI deployment.
- Knowledge of legal industry regulations around data privacy, confidentiality, and privilege.
- Experience managing enterprise\-level budgets exceeding $5M annually.
- Background in vendor management and contract negotiation for SaaS/AI platforms.
- Familiarity with prompt engineering, AI fine\-tuning, and retrieval\-augmented generation (RAG) architectures.
Salary Information
NY Only: The estimated base salary range for this position is $150,000 to $180,000 at the time of posting.
The actual salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location in which the applicant lives and/or from which they will be performing the job. This role is exempt meaning it is not overtime pay eligible.
Simpson Thacher will not sponsor applicants for work visas for this position.
Privacy Notice
For information about how Simpson Thacher \& Bartlett LLP collects and processes your personal information, please refer to our Privacy Notice available at https://www.stblaw.com/other/privacy\-notice .
Simpson Thacher \& Bartlett is committed to a collegial work environment in which all individuals are treated with respect and dignity. The Firm prohibits discrimination or harassment based upon race, color, religion, gender, gender identity or expression, age, national origin, citizenship status, disability, marital or partnership status, sexual orientation, veteran’s status or any other legally protected status. This Policy pertains to every aspect of an individual’s relationship with the Firm, including but not limited to recruitment, hiring, compensation, benefits, training and development, promotion, transfer, discipline, termination, and all other privileges, terms and conditions of employment.
\#LI\-Hybrid
Salary Context
This $150K-$180K range is below the median for AI Product Manager roles in our dataset (median: $185K across 167 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Simpson Thacher & Bartlett LLP, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($165K) sits 24% below the category median. Disclosed range: $150K to $180K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Simpson Thacher & Bartlett LLP AI Hiring
Simpson Thacher & Bartlett LLP has 1 open AI role right now. They're hiring across AI Product Manager. Based in New York, NY, US. Compensation range: $180K - $180K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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