Executive Director, Responsible AI & Enterprise Governance

$255K - $424K Tarrytown, NY, US Mid Level AI Safety

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About This Role

AI job market dashboard showing open roles by category

Build our future together:

At Regeneron, we use science and innovation to develop life\-changing medicines for people with serious diseases. We're looking for an Executive Director, Responsible AI \& Enterprise Governance to join our fast\-moving Enterprise Data \& AI organization. You'll build and run our enterprise AI governance framework, setting the policies, standards, and controls that let Regeneron move fast with confidence, auditability, and trust. You'll partner closely with Legal, Compliance, and the CISO to keep AI use safe, compliant, and aligned with our values. This role reports to the SVP, Chief AI Officer, and offers the chance to shape governance as an accelerant for AI adoption, not a barrier to it.

### When \& where:

  • Location: Sleepy Hollow, New York
  • Work model/flexibility: 4 days a week on\-site

### Discover your role:

  • Build and maintain Regeneron's enterprise AI policy framework, keeping it practical and enforceable
  • Own the AI risk taxonomy, classifying use cases and setting controls that match their risk level
  • Embed ethics and fairness principles into how AI systems are designed, built, and evaluated
  • Set standards for AI transparency and explainability that hold up to regulators and stakeholders
  • Track the AI regulatory landscape across FDA, EMA, and the EU AI Act
  • Own GxP AI system validation and audit, keeping regulated systems audit\-ready
  • Assess AI vendors and platforms for governance, transparency, and risk
  • Lead the enterprise AI incident management framework, from escalation through remediation

This role might be for you if you:

  • Have built governance frameworks for AI or data systems in a complex, regulated enterprise
  • Bring deep knowledge of AI risk, ethics, and model governance, with real\-world experience putting it into practice
  • Understand GxP validation requirements in a life sciences or biopharma setting
  • Stay current on the AI regulatory landscape, including FDA AI/ML guidance and the EU AI Act
  • Have enough technical depth in generative AI and LLM architecture to govern these systems with credibility
  • Communicate and build trust across Legal, Compliance, Regulatory Affairs, and business leadership
  • See governance as something that enables speed and trust, not something that slows things down
  • Enjoy developing senior governance and risk talent

### This role requires:

  • A Bachelor's degree in a related field (advanced degree required for certain scientific or clinical positions)
  • 17\+ years of experience in AI governance, risk management, regulatory affairs, or compliance

Does this sound like you? Apply now to take your first step towards living the Regeneron Way! We are committed to building a workplace with an inclusive culture. Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, sexual orientation, gender identity or expression, gender reassignment, marital or civil partnership status, civil status, pregnancy or parental status, age, disability, nationality, citizenship status, ethnic or national origin, membership of the Traveler community, familial status, genetic information, military or veteran status, or any other characteristic protected under applicable law. Where required, we will provide reasonable accommodation to applicants with known disabilities or chronic illnesses during the recruitment process, unless such accommodation would impose undue hardship.

Where necessary, we disclose salary ranges for roles in all countries in which we operate. The final offer will be determined within the relevant range based on the country of employment, specific role level, and your skills and experience. In some countries, collective bargaining agreements (CBAs) may apply and influence certain elements of pay or benefits. Regeneron offers a competitive and comprehensive total rewards package which may include, depending on country and role: annual bonuses or other incentive plans, equity awards, pension or retirement benefits, 401(k) company match, health and wellness programs, fitness centers, insurance benefits (e.g. medical, dental, vision, life and disability), paid time off, and family support benefits. For additional information about Regeneron benefits in the U.S., please visit https://careers.regeneron.com/en/working\-at\-regeneron/total\-rewards/. For other locations, additional information will be provided during the recruitment process. If you have any questions, please speak with your recruiter.

Please be advised that at Regeneron, we believe we do our best work when we are together. For that reason, many roles are required to be performed on‑site. Please speak with your recruiter and hiring manager for more information about on‑site expectations for your role and location.

As part of the recruitment process, certain background checks may be conducted in accordance with the laws of the country where the position is based. The purpose of such checks is to verify certain information prior to the commencement of employment such as identity, right to work and educational qualifications.

For jobs in Canada: this posting is for an existing position.

Salary Range (annually)

$255,000\.00 \- $424,900\.00

Salary Context

This $255K-$424K range is above the 75th percentile for AI Safety roles in our dataset (median: $262K across 8 roles with salary data).

Role Details

Company Regeneron
Title Executive Director, Responsible AI & Enterprise Governance
Location Tarrytown, NY, US
Category AI Safety
Experience Mid Level
Salary $255K - $424K
Remote No

About This Role

This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.

The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.

Across the 4,317 AI roles we're tracking, AI Safety positions make up 0% of the market. At Regeneron, this role fits into their broader AI and engineering organization.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

What the Work Looks Like

Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

Skills in Demand for This Role

Python (52% of roles) Aws (28% of roles) Azure (22% of roles) Rag (21% of roles) Gcp (15% of roles) Pytorch (15% of roles) Prompt Engineering (14% of roles) Kubernetes (13% of roles)

Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.

Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.

Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

Compensation Benchmarks

AI Safety roles pay a median of $287,500 based on 34 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($339K) sits 18% above the category median. Disclosed range: $255K to $424K.

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 Research Engineer ($272,100) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.

Regeneron AI Hiring

Regeneron has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Safety. Based in Tarrytown, NY, US. Compensation range: $360K - $424K.

Location Context

Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).

Career Path

Common paths into AI Safety roles include Software Engineer, Data Scientist, Data Analyst.

From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.

Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.

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: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

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 hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

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

Based on 34 roles with disclosed compensation, the median salary for AI Safety positions is $287,500. Actual compensation varies by seniority, location, and company stage.
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Regeneron is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Safety positions include Senior Engineer, AI Architect, Engineering Manager, Principal Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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