Product Manager, Patient Messaging

Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.

Position Summary

Join athenahealth's Patient Experience (PEX) division as a Product Manager for the Patient Messaging Zone in Bangalore. In this role, you will own a defined product area within Patient Messaging, driving the roadmap for AI-enabled communication capabilities that help patients and care teams connect efficiently and safely. You will work closely with engineering, data science, UX, and analytics teams to deliver messaging experiences that are usable, trustworthy, and grounded in responsible use of AI. This role partners closely with US-based product peers and reports to the Zone's product leadership in Bangalore.

About the Team

The Patient Messaging Zone brings together Product Management, Engineering, UX, Product Analytics, Data Science, and Patient Safety partners to improve how patients and provider staff communicate. The team is expanding its use of AI to reduce staff burden while keeping patients safe and informed. This role will help shape product decisions for an assigned area within that portfolio, working in close partnership with the Bangalore development organization and US stakeholders.

Essential Job Responsibilities

Product Strategy & AI-Enabled Delivery

• Define and manage the product strategy and roadmap for an assigned area within Patient Messaging.
• Learn users workflows (patients, front-desk/clinical staff) and propose AI-enabled solutions that reduce friction and improve response times.
• Collaborate with data science and engineering to shape AI features ensuring they are measurable and appropriate for patient-facing communication.
• Define expected behavior for AI-enabled capabilities, including guardrails for trust, explainability, escalation to a human, and handling of low-confidence outputs.
• Write clear user stories, acceptance criteria, and product requirements that support engineering delivery, including requirements specific to model behavior, edge cases, and fallback paths.
• Use AI-enabled tools and product analytics to inform requirements, evaluate tradeoffs, and speed up decision-making across planning and delivery.

Cross-Functional Execution

• Work with engineering and scrum teams to prioritize backlog items and guide day-to-day delivery in an Agile environment.
• Partner with cross-functional teams to evaluate customer needs, market trends, and competitive signals relevant to patient messaging and conversational AI.
• Contribute to product discovery: identifying problems, testing concepts, and validating solutions (including AI-generated outputs) with users and stakeholders.
• Monitor product and model performance after release use feedback, quality metrics, and user input to guide iterative improvement.
• Support launch planning, alpha/beta feedback cycles, adoption activities, and resolution of production issues.
• Represent the voice of the customer in product and design discussions, balancing efficiency gains from AI against patient safety and data sensitivity considerations.
• Coordinate with legal, compliance, security, and patient safety partners on responsible-AI review processes for messaging features.

Collaboration Across Geographies

• Work closely with US-based product peers to align on workflow design, requirements, and roadmap sequencing.
• Contribute to measurement frameworks for feature and model performance within the zone.
• Support continuous improvement efforts across the product lifecycle, including documentation of AI feature behavior for internal and client-facing teams.

Expected Education & Experience

• Bachelor's degree required a degree in Computer Science, Data Science, Business, or a related field preferred.
• 8+ years of product management experience healthcare or health technology experience preferred.
• Strong understanding of AI/ML concepts and how they apply to product delivery, including familiarity with model lifecycle concepts (training, validation, deployment, monitoring).
• Understanding of responsible AI principles - bias, explainability, human oversight, and trust.
• Familiarity with data pipelines, data quality considerations, and experimentation methods (e.g., A/B testing of model-driven features).
• Experience bringing AI-driven or data-intensive products to market and supporting adoption post-launch.
• Technical understanding of mobile, SaaS, messaging infrastructure, and APIs sufficient to assess feasibility and timelines.
• Strong written and verbal communication skills, with the ability to translate complex AI/technical concepts for non-technical stakeholders.
• Comfortable gathering requirements from globally distributed teams and coordinating delivery across geographies.