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About This Role
Director, Omnichannel Strategy, AI & Customer Engagement, Endocrinology
ID: 2906 Date of Posting: Oct 19, 2026 Business Area: Sales & Marketing Job Type: Direct Employee On site / Remote / Hybrid: On Site Hub Office: Bridgewater, NJ, US Territory: N/A Full-Time or Part-Time: Full Time Seniority: Director At Recordati, we are united by a clear purpose: unlocking the full potential of life. With a century of history behind us, we are building the next chapter of our journey, continuing to grow while keeping patients at the centre of all we do.
What drives us is a shared belief that health, and the opportunity to live life to the full, should be within reach for everyone. This brings energy to our work, shaping how we support each other and show up every day. Our values – Better Together, Never Settle and Always Deliver – reflect this mindset, helping us to keep improving and make a meaningful difference.
Above all, these values bring to life our promise to everyone at Recordati, you can unlock your full potential. We know that people thrive when they can be themselves, are trusted and supported, and are given the opportunity to grow and make a meaningful contribution.
Are you ready to unlock your full potential?
This position is with Recordati Rare Diseases, Inc. (RRD), North America, an affiliate of Recordati.
Recordati Rare Diseases, Inc. (RRD) develops high-impact therapies for devastating rare diseases, focusing on providing often overlooked treatments to underserved communities in the U.S. Our mission is to mitigate the impact of rare diseases through increased awareness, improved diagnoses, and enhanced treatment availability, covering endocrinology, metabolic, and oncology franchises. RRD is dedicated to excellence, fostering a dynamic work environment that promotes professional growth and a significant impact on patients' lives.
Reporting Structure
Reports To: Senior Director Marketing - Endocrinology
Direct Reports: N/A
Areas Managed: Consultation Patient Health Care Professional (HCP) Marketing and Disease Education for assigned brands Consultation Health Care Professional (HCP) marketing and disease education for assigned brands Salesforce promotion and field support Omni-channel and AI Patient and HCP marketing (print, digital, social) Patient advocacy groups, medical society, congress, conference strategy and management Competitive intelligence Support Senior Director of Marketing
Overview
The Director, Omnichannel Strategy, AI & Customer Engagement leads the development and execution of integrated customer engagement strategies across the endocrinology franchise, with primary responsibility for Cushing’s syndrome and acromegaly. This leader is accountable for creating personalized, data-driven engagement strategies that improve customer experience, strengthen relationships with healthcare professionals (HCPs), patients, and caregivers, and drive commercial performance. Working closely with Brand Marketing, Sales, Medical Affairs, Market Access, Patient Services, Digital, Analytics, and Commercial Operations, the Director will build omnichannel engagement capabilities that optimize customer interactions throughout the treatment journey while ensuring compliance with regulatory and legal requirements. This position requires a strategic marketer with strong pharmaceutical commercial experience, exceptional cross-functional leadership skills, and expertise in customer engagement, digital marketing, Agentic AI incorporation, CRM, Next Best Action, Media and advanced analytics.
Essential Duties and Responsibilities
- Develop and lead the integrated customer engagement strategy across the endocrinology portfolio.
- Design personalized omnichannel engagement plans aligned with brand objectives and customer preferences.
- Translate brand strategy into measurable customer experiences across digital and personal channels.
- Develop customer journey maps for healthcare professionals, patients, caregivers, and office staff.
- Identify unmet customer needs and opportunities to improve engagem
- Integrate Agentic AI analytics, content development, Next Best Action
- Leverage customer data, segmentation, and behavioral analytics to optimize engagement.
- Partner with Commercial Analytics to develop dashboards and KPIs.
- Use customer insights to continuously improve campaign effectiveness.
- Apply AI-enabled insights where appropriate to personalize customer interactions.
- Monitor omnichannel performance metrics and recommend optimization strategies.
- AI-enabled personalization
- Marketing automation
- Next Best Action recommendations
- CRM optimization
- Content personalization
- Digital measurement frameworks
- Manage digital agencies and marketing partners.
- Oversee campaign development from strategy through execution.
- Manage agency budgets and performance expectations.
- Ensure projects are delivered on time and within budget.
Education and Experience
- Bachelor’s degree required; MBA preferred.
- 10+ years of pharmaceutical or biotechnology commercial experience.
- 5+ years of pharmaceutical marketing experience.
- Experience leading omnichannel customer engagement programs.
- Experience launching or marketing specialty pharmaceuticals.
- Demonstrated success working within highly regulated environments.
- Strong understanding of CRM platforms (Veeva CRM, Salesforce).
- Experience using customer analytics and marketing automation.
- Strong project management and leadership skills.
Knowledge and Skills
- Strong marketing acumen: strategy, market research, segmentation, brand positioning, tactical plan development
- Passion and empathy for building meaningful experiences with patient and HCPs
- Analytical mindset with ability to derive insights from data
- Graphic and organizational support for presentations; narrative storytelling
- Experience with Canva, Power Point, slide making
- Creativity and innovation, with analytical problem-solving skills
- Omni-channel program management and support
- Experience using GenAI tools for content creation
- Highly organized with the ability to manage multiple priorities
- Action-oriented, collaborative, and comfortable operating with autonomy
- Adaptable and effective in a fast-paced, evolving environment
Work Environment
This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines. Based upon job requirements, employee may be required at times to attend meetings including travel out of state over weekends and nights. Employee must be able to freely operate and travel by car and train/plane modes of transportation. Employee is required to have a valid driver’s license and means of transportation.
Physical Demands
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The employee must be able to fly via commercial air carrier. This is largely a sedentary role; however, the employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms; talk and hear. Occasionally it is required to lift and/or move light to moderate weight up to 25 lbs.
Location/Travel
- This position is based at RRD’s Headquarters in Bridgewater, NJ.
- Approximately 20 % of travel is required
FLSA Classification
- This position is considered Exempt.
EEO Statement
It is the policy of Recordati Rare Diseases to provide equal employment opportunity (EEO) to all persons regardless of race, color, religion, sex, sexual orientation, gender identity, or national origin. Further, Recordati Rare Diseases will not discriminate on the basis of any characteristic protected by federal, state, or local law. Recordati Rare Diseases will provide reasonable accommodation for qualified individual with disabilities.
Disclaimer
The expected base salary range for this position is $190,000 to $250,000 per year. The actual salary offered will be determined based on job-related factors, including experience, qualifications, skills, internal equity, market conditions, and work location.
This position is eligible to participate in the company's annual performance-based incentive program, subject to the terms of the applicable plan. Eligible employees receive benefits including medical, dental, and vision coverage; a 401(k) plan with company contributions; life and disability insurance; paid time off and holidays; and paid and unpaid leave programs. Eligibility is subject to applicable plan terms and company policies.
#LI-DV1
At Recordati we believe in people! Inspired by our purpose - unlocking the full potential of life - we are committed to creating a diverse environment and cultivating a culture of inclusion. We strive to continually lead with our values and beliefs, enabling our employees to bring their whole selves to work and develop their potential.
We are proud to be an equal opportunity employer. We recruit, develop and reward without regard to, amongst others, gender, sexual orientation, gender identity or expression, national origin, age, physical or mental ability, race, ethnicity, political or religious belief.
If you are looking to join a company where you can try new things, speak openly, and be bold, we invite you to apply today.
Salary Context
This $190K-$250K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Recordati S.p.A, 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 Required
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 $212,040 based on 13,780 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. Disclosed range: $190K to $250K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Recordati S.p.A AI Hiring
Recordati S.p.A has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Bridgewater, NJ, US. Compensation range: $250K - $250K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 median, while Prompt Engineer roles sit at $140,000. 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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