Vice President, Technology and Product (Remote)

M3USA•Fort Washington, PA

2d•Remote

About The Position

We are seeking an experienced VP of Product and Technology to build and launch our next generation of physician engagement products and services. This is a builder role at the intersection of product and engineering. You will develop fresh ideas for how pharma brands can reach physicians and be useful to them, and you will be measured on impact, not output. Reporting to the Chief Commercial Officer, you will oversee all technology initiatives, manage product and engineering teams, and architect scalable solutions that enhance our ability to deliver timely, relevant experiences to healthcare professionals in the US. You will enable the team to take advantage of the speed and agility of agentic code development to prototype and pivot fast and collaborate with other teams to find optimal solutions through working prototypes, not wireframes and powerpoints. The ideal candidate is a technologist who has led product, design, and engineering as one integrated team under a single reporting line. You are credible with engineers on architecture, data infrastructure, and AI, and you own the full process from discovery and design through development, release, and iteration. You have built engagement products that people return to by choice: interactive formats, habit loops, community, and personalization. You have taken a product from 0 to 1, and you have set up and run a forward-deployed engineering (FDE) model across a range of business stakeholders.

Requirements

12+ years in product and engineering, including 5+ years leading product, design, and engineering as one integrated team, with managers reporting to you.
A product you took from 0 to 1, from first idea through first paying customers, as a founder, early employee, or leader of a new venture inside a larger company, with specific, measurable results.
Engagement products with proven retention: interactive, community, or personalized experiences, with evidence of how they changed return visits and depth of engagement.
A forward-deployed engineering (FDE) model, or a comparable embedded model, that you set up and ran, with engineers working directly alongside clients and business stakeholders.
Architecture: you have made and owned the architecture decisions for a high-traffic production platform with high availability requirements, on modern cloud and event-driven infrastructure (AWS preferred).
AI-native development: your teams build with AI coding agents as standard practice, and you can show the effect on cycle time and output.
Production AI: LLM applications, recommendation systems, and real-time personalization shipped to users, not only piloted.
First-party data: event instrumentation, identity resolution, unified profiles, and activation through a customer data platform, designed privacy-first.
Experimentation and measurement: A/B testing, feature flags, and rollback infrastructure, plus the statistical judgment to separate real signal from noise. You know the difference between engagement metrics and insight into what users know and believe.

Responsibilities

Own the MDLinx product vision and roadmap across physician-facing experiences and pharma engagement products, leading product, design, and engineering as one team.
Bring new ideas for how pharma brands can reach and help physicians, and for experiences physicians return to by choice.
Build a culture of rapid experimentation: go from idea to working prototype in days, put it in front of physicians and clients, learn, and redeploy.
Spend regular time with physicians and pharma clients and let what you learn in the field shape what the team builds next.
Run a forward-deployed engineering (FDE) model in which engineers work directly with internal business stakeholders and clients. Client engagements become live prototypes, and what proves valuable becomes a platform capability.
Scale what works, retire what doesn’t, and quickly move people and code to the next bet.
Lead application development and data engineering, directly and through team leads.
Keep teams small, fast, and focused on outcomes. Buy or reuse wherever something isn’t a differentiator.
Make AI-native development the default way the team works. Ship AI capabilities (personalization, recommendation, content intelligence) as core parts of the product.
Build a platform designed for speed, so teams can launch, test, and roll back experiments without destabilizing core products.
Run MDLinx product and technology with a high degree of autonomy, within M3 USA engineering standards and in line with the M3 USA technology plan.
Instrument every experience to generate signal, giving us a continuous read on physician knowledge, attitudes, and behavior.
Own the MDLinx first-party data strategy with the data engineering team, serving both product and commercial needs.
Lead generative AI for content creation, summarization, curation, and medical literature analysis.
Build recommendation and real-time personalization engines, plus predictive models for content affinity and engagement propensity.
Own technical direction and architecture, using a modular, composable platform built for rapid deployment and experimentation.
Architect the infrastructure to capture, unify, and activate physician behavioral signals, including unified physician profiles, for both product and commercial use.
Keep teams small and fast, ship in days rather than quarters, and hold the team to results that matter to physicians and clients.
Make sharp calls on what to test next and act quickly on the evidence: scale, retire, or redeploy.
Treat Editorial, Sales, and Marketing as co-builders, and you explain technical tradeoffs clearly to engineers, physicians, pharma clients, and executives.
Operate with autonomy inside a larger organization, moving at startup speed within M3 USA standards.