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Senior Director, AI \& Data Solutions
Position Summary:
Desired Location: Bridgewater, NJ or Morrisville/Durham, NC, with ability to travel 20%
The Senior Director, AI \& Data Solutions enables Catalent to move from AI experimentation to scaled, production\-ready solutions that improve cost, productivity, quality, and decision\-making. This role translates business priorities into enterprise AI, data, and analytics capabilities; builds the operating model needed to govern and scale them; and ensures solutions are embedded into real workflows where they deliver measurable value. The position reports to the VP, Digital Transformation. The role is expected to partner closely with senior leaders across Operations, Quality, Sales, Marketing, Finance, IT/Digital, Information Security, Legal and Compliance to align AI and data priorities with enterprise business outcomes.
This is an opportunity to shape how AI and data are used at enterprise scale within a global life sciences organization. The successful candidate will help establish the roadmap, governance, platforms, delivery model and business adoption discipline required to turn high\-potential AI ideas into reusable, compliant and measurable capabilities that improve how Catalent operates.
The Role:
Strategy and Roadmap
- Define and execute Catalent’s enterprise AI and data roadmap, prioritizing use cases by business value, feasibility, and strategic fit.
- Translate enterprise and functional priorities into AI, data and analytics capabilities that deliver expected value across productivity, quality, cost, cycle time, growth and better decision\-making.
Delivery and Value Creation
- Own the end\-to\-end delivery of high\-value AI, data, and analytics solutions, from discovery and design through deployment, adoption, and value tracking.
- Embed AI and data solutions into real business workflows, ensuring active business ownership, clear adoption plans, measurable success criteria and sustained usage after deployment.
- Build reusable solution patterns, platforms and delivery methods that allow successful AI and data capabilities to scale across Catalent.
Governance and Responsible AI
- Establish and oversee enterprise AI and data governance to ensure responsible use, data quality, security, privacy, compliance, regulatory alignment, lifecycle management, and accountability across AI and data assets.
- Champion ethical and responsible AI practices by partnering with Security, Legal, Compliance, Quality, and business stakeholders to ensure appropriate governance, transparency, human oversight, auditability, validation, and model risk management
Leadership and Organization Capability
- Build, lead and develop a high\-performing AI and Data organization with the skills, discipline and business orientation required to scale impact across Catalent.
- Create strong partnerships across business, technology, data, security, legal and compliance teams to ensure solutions are practical, adopted and sustainable.
- Manage internal teams, external partners and vendors effectively, ensuring delivery quality, value for money and alignment to Catalent’s enterprise standards.
- Other duties as assigned.
The Candidate:
- Bachelor’s Degree in Computer Science, Engineering, Information Systems, or related field;
- 5\+ years of experience in AI, data, digital product development, software engineering, or technology\-enabled transformation.
- Demonstrated ability to translate business strategy into technology roadmaps, investment priorities, and executable delivery plans.
- Strong understanding of AI technologies, data platforms, analytics, cloud and hybrid architectures, Agile delivery, and modern integration patterns such as microservices, service\-oriented architecture, and event\-based architecture.
- Working knowledge of information architecture, data governance, master data management, business intelligence, data warehouse design, and data science concepts.
- Experience building and leading high\-performing teams across AI, data, analytics, product, architecture, Engineering or solution delivery disciplines.
- Understanding compliance, validation, privacy, information security, quality and operational risk considerations relevant to AI and data solutions in regulated settings.
- Ability to travel up to 20% of the time.
- Demonstrable leadership experience at Catalent (including but not limited to participation in Catalent‑sponsored leadership programs such as NGGL, GOLD, LEAD Now, GM Excellence, and GROW) may be considered in place of external experience.
Preferred Skills \& Background
- Advanced Degree
- Preferred experience in pharmaceutical, life sciences, or other regulated environments.
Pay
The anticipated salary range for this position in New Jersey is $500,000\-$600,000 plus an annual bonus target. The final salary offered to a successful candidate may vary, and will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, skillset, education, business needs, etc. Catalent is a multi\-state employer, and this salary range may not reflect positions that work in other states.
Why You Should Join Catalent:
- Defined career path and annual performance review and feedback process.
- Diverse, inclusive culture.
- Potential for career growth on an expanding team within an organization dedicated to preserving and bettering lives.
- Competitive paid time off plus 8 paid holidays.
- Community engagement and green initiatives.
- Medical, dental, and vision benefits effective day one of employment.
- Tuition reimbursement.
Catalent offers rewarding opportunities to further your career! Join the global drug development and delivery leader and help us bring over 7,000 life\-saving and life\-enhancing products to patients around the world. Catalent is an exciting and growing international company where employees work directly with pharma, biopharma and consumer health companies of all sizes to advance new medicines from early development to clinical trials and to the market. Catalent produces more than 70 billion doses per year, and each one will be used by someone who is counting on us. Join us in making a difference.
personal initiative. dynamic pace. meaningful work.
Visit Catalent Careers to explore career opportunities.
Catalent is an Equal Opportunity Employer, including disability and veterans.
If you require reasonable accommodation for any part of the application or hiring process due to a disability, you may submit your request by sending an email, and confirming your request for an accommodation and include the job number, title and location to [email protected]. This option is reserved for individuals who require accommodation due to a disability. Information received will be processed by a U.S. Catalent employee and then routed to a local recruiter who will provide assistance to ensure appropriate consideration in the application or hiring process.
Notice to Agency and Search Firm Representatives: Catalent Pharma Solutions (Catalent) is not accepting unsolicited resumes from agencies and/or search firms for this job posting. Resumes submitted to any Catalent employee by a third party agency and/or search firm without a valid written \& signed search agreement, will become the sole property of Catalent. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. Thank you.
Important Security Notice to U.S. Job Seekers:
Catalent NEVER asks candidates to provide any type of payment, bank details, photocopies of identification, social security number or other highly sensitive personal information during the offer process, and we NEVER do so via email or social media. If you receive any such request, DO NOT respond— it is a fraudulent request. Please forward such requests to [email protected] for us to investigate with local authorities.
California Job Seekers can find our California Job Applicant Notice HERE.
Salary Context
This $500K-$600K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Catalent Pharma Solutions, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($550K) sits 156% above the category median. Disclosed range: $500K to $600K.
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.
Catalent Pharma Solutions AI Hiring
Catalent Pharma Solutions has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Morrisville, NC, US. Compensation range: $600K - $600K.
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/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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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