Vice President, Technology and Product (Remote)

M3USA•Fort Washington, PA

4d•Remote

About The Position

MDLinx, an M3 company, is seeking a Vice President, Technology and Product to join their team. This role will be responsible for defining and executing the technology roadmap with a focus on AI-driven personalization and content intelligence. The ideal candidate will champion a rapid prototyping and experimentation culture, partner with various teams to translate business needs into technical solutions, and lead AI/ML initiatives. Responsibilities include building robust community platforms, developing a comprehensive MarTech stack, architecting first-party data infrastructure, and implementing real-time personalization engines. The role also involves building and managing a high-performing engineering organization, fostering a culture of continuous learning, and implementing agile development practices. A key focus will be on building a comprehensive first-party data strategy, implementing a customer data platform, and creating data clean rooms for secure collaboration. The position will lead AI transformation, focusing on generative AI for content creation and summarization, and implementing LLMs for automated medical literature analysis. The role will also design and implement features for the physician community, including social layers, gamification, and user-generated content platforms. Vendor and stakeholder management, including evaluating MarTech vendors and building strategic partnerships, is also a critical aspect of this role. The company is a Japanese global leader in providing technological and research solutions to the healthcare industry, with a significant global presence and a publicly traded entity on the Tokyo Stock Exchange.

Requirements

7+ years of progressive technology leadership experience, with at least 3 years managing engineering teams.
Proven track record in digital publishing, content management, or healthcare technology sectors.
Experience scaling platforms serving millions of users with high availability requirements.
Demonstrated success in AI/ML implementation and rapid prototyping initiatives.
Background in building experimentation frameworks and data-driven product development.
Track record in community platform development and user-generated content systems.
Deep understanding of AI/ML platforms, LLMs, and generative AI applications.
Experience with MarTech ecosystems (CDCDPs, DMPs, marketing automation, attribution).
Proficiency in building community platforms and user-generated content systems.
Strong background in experimentation platforms and feature flagging systems.
Knowledge of first-party data strategies, identity resolution, and privacy-compliant targeting.
Experience with real-time personalization, recommendation engines, and predictive analytics.
Familiarity with modern cloud platforms (AWS preferred) and event-driven architectures.
Strategic vision balanced with hands-on experimentation and a rapid iteration mindset.
Strong advocate for data-driven decision making and hypothesis-driven development.
Ability to build and champion a test-and-learn culture across the organization.
Excellent communication skills for engaging with both technical and non-technical stakeholders.
Experience driving growth through technical innovation and rapid market testing.
Track record of building high-velocity engineering teams focused on business impact.

Nice To Haves

Experience building professional communities or social platforms in healthcare/medical sectors.
Background in programmatic advertising, ad tech, and yield optimization.
Knowledge of Customer Data Platforms (Segment, mParticle, Adobe Experience Platform).
Experience with rapid prototyping methodologies (Design Sprints, Lean Startup).
Track record implementing generative AI in production environments.
Familiarity with healthcare data interoperability standards (FHIR, HL7).
Experience with growth engineering and conversion rate optimization.
Background in building developer ecosystems and API marketplaces.
Previous experience in private equity portfolio companies or high-growth environments.

Responsibilities

Define and execute the technology roadmap with a focus on AI-driven personalization and content intelligence.
Champion rapid prototyping and experimentation culture across engineering and product teams.
Partner with Product, Editorial, Sales, and Marketing teams to translate business needs into technical solutions.
Lead AI/ML initiatives for content curation, recommendation engines, and predictive physician engagement.
Establish an experimentation framework with an A/B testing infrastructure and data-driven decision-making.
Drive innovation sprints and hackathons to accelerate the development of new features.
Build robust community platforms enabling peer-to-peer engagement among healthcare professionals.
Develop a comprehensive MarTech stack integrating CDP, marketing automation, and omnichannel orchestration.
Architect first-party data infrastructure to capture, unify, and activate physician behavioral signals.
Design scalable APIs and integration layers for pharmaceutical partner platforms and data exchanges.
Implement real-time personalization engines leveraging machine learning and behavioral targeting.
Create a modular, composable architecture supporting rapid feature deployment and experimentation.
Ensure platform reliability, security, and compliance with healthcare industry standards (HIPAA, etc.).
Build and scale a high-performing engineering organization embracing experimentation and innovation.
Foster a culture of rapid prototyping, fail-fast mentality, and continuous learning.
Establish innovation time (20% projects) and regular hackathons for creative exploration.
Implement agile development with emphasis on quick iterations and the MVP approaches.
Create cross-functional pods combining engineering, data science, and growth teams.
Partner with HR on talent acquisition, focusing on AI/ML and growth engineering expertise.
Build a comprehensive first-party data strategy to create a competitive advantage in physician engagement.
Develop unified physician profiles aggregating behavioral, preference, and interaction data across touchpoints.
Implement a customer data platform (CDP) for real-time audience segmentation and activation.
Create data clean rooms for secure collaboration with a pharmaceutical partners.
Design privacy-first architecture supporting targeted advertising without third-party cookies.
Build predictive models for content affinity, engagement propensity, and lifetime value.
Lead AI transformation with a focus on generative AI for content creation and summarization.
Implement LLMs for automated medical literature analysis and insight extraction.
Develop an experimentation platform that enables the rapid testing of new features and algorithms.
Create an innovation lab for exploring emerging technologies (voice interfaces, AR/VR, etc.).
Build ML pipelines for automated content tagging, classification, and knowledge graphs.
Foster a fail-fast mentality with a structured approach to proof-of-concepts and MVPs.
Design and implement features for the physician community, enabling peer collaboration and knowledge sharing.
Build social layers, including discussion forums, case studies, and peer review systems, to foster a collaborative environment.
Develop gamification strategies to increase engagement and platform stickiness.
Create user-generated content platforms with moderation and quality control systems.
Implement social proof mechanisms (ratings, reviews, endorsements) for content and CME programs.
Build referral and advocacy programs leveraging network effects.
Evaluate and integrate best-in-class MarTech vendors across the marketing technology stack.
Build strategic partnerships with AI/ML platform providers and data enrichment services.
Manage relationships with advertising technology partners for programmatic capabilities.
Collaborate with M3 global technology teams on shared AI initiatives and data strategies.
Present the technology strategy and experimentation results to the board and executive stakeholders.
Optimize technology spend with a focus on ROI from rapid prototyping and MVP validation.