About this role
This role is for one of Weekday’s clients
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Experience
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4+ years
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Location: Bangalore
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JobType: full-time
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We are looking for an experienced and user-focused Product Manager to build and scale AI-powered healthcare products that help people navigate complex health information with greater clarity, confidence, and trust.
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The product serves as a digital health companion, enabling users to understand symptoms, laboratory reports, prescriptions, medications, and health-related concerns between doctor visits. The broader vision is to build intelligent clinical AI systems with advanced reasoning, memory, safety, and workflow capabilities that can support increasingly complex healthcare tasks.
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This is a high-ownership role for a product leader who can work from first principles, navigate ambiguity, and translate complex clinical and technical concepts into intuitive, reliable, and empathetic user experiences. You will lead product initiatives end-to-end, collaborating closely with founders, engineers, designers, AI specialists, and clinical teams to build AI-native healthcare experiences that are safe, useful, and trusted.
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Requirements
Key Responsibilities
1. Product Strategy and Ownership
- Own product areas end-to-end, from problem discovery and user research to product strategy, requirements, execution, launch, and continuous iteration.
- Define product vision, roadmaps, user journeys, success metrics, and launch strategies aligned with customer needs and business objectives.
- Lead 0-to-1 product development initiatives, turning ambiguous problem statements into validated solutions and production-ready experiences.
- Partner with founders and cross-functional teams to prioritise opportunities and establish a strong product direction.
- Drive product decisions using first-principles thinking, data, user feedback, and sound product judgment.
2. AI-Powered Healthcare Experiences
- Build and improve patient-facing experiences for symptom assessment, laboratory report interpretation, prescriptions, medication guidance, health history, care navigation, and follow-ups.
- Design AI-native interaction patterns, including conversational interfaces, structured information cards, contextual memory, explainability, uncertainty communication, and escalation workflows.
- Translate complex clinical reasoning into clear, actionable, and easy-to-understand experiences without compromising accuracy or nuance.
- Define how the product communicates potential causes, risk levels, supporting evidence, safety warnings, and recommended next steps.
- Develop personalised and longitudinal health experiences that help users maintain continuity across healthcare interactions.
3. Clinical Safety, Trust, and Privacy
- Design product experiences that communicate the capabilities and limitations of AI clearly and responsibly.
- Build workflows for user consent, privacy controls, data management, emergency handling, escalation, and human clinical oversight.
- Ensure the product handles uncertainty appropriately and guides users towards professional care when necessary.
- Collaborate with clinical and technical teams to establish appropriate safeguards, quality standards, and escalation mechanisms.
- Incorporate safety, reliability, accessibility, and user trust into product requirements and release decisions.
4. Human Oversight and Clinical Workflows
- Design workflows that enable doctors, clinical reviewers, and internal teams to inspect cases, review escalations, provide feedback, and audit AI behaviour.
- Identify opportunities to improve clinical workflows through AI-enabled automation and human-in-the-loop processes.
- Work with clinical stakeholders to understand operational constraints and translate them into practical product solutions.
- Establish feedback loops that improve product quality, clinical relevance, and the reliability of AI-generated experiences.
5. Product Execution and Continuous Improvement
- Write clear product requirements, define information architecture, and collaborate with engineering and design teams to deliver high-quality experiences.
- Lead product development across mobile, web, messaging-adjacent experiences, internal tools, and emerging clinical workflows.
- Define and monitor product metrics to evaluate engagement, usability, quality, safety, and customer outcomes.
- Use quantitative data, user research, qualitative feedback, and clinical insights to validate assumptions and improve product decisions.
- Drive rapid experimentation and iteration while maintaining a high standard of product quality.
- Help establish product operating processes, collaboration practices, and quality benchmarks across the organisation.
Required Qualifications and Experience
- 5+ years of experience in product management, with a strong track record of building and scaling user-facing products.
- Experience taking products from 0 to 1, including problem discovery, prototyping, validation, launch, and post-launch optimisation.
- Proven ability to manage complex workflows, multi-step user journeys, or products serving specialised user groups.
- Experience building AI-first, conversational, or context-aware product experiences is highly desirable.
- Strong analytical skills and the ability to use data, research, and customer feedback to inform product decisions.
- Excellent written and verbal communication skills, with the ability to explain complex ideas to technical and non-technical stakeholders.
- Demonstrated ability to work independently, manage ambiguity, and take ownership of broad product initiatives.
- Experience in healthcare technology or other high-stakes product environments is an advantage.
Must-have Skills
- Product Management
- Artificial Intelligence (AI)
- B2C Product Development
- Product Strategy and Roadmap Ownership
- 0-to-1 Product Development
- User Research and Product Discovery
- Data-driven Decision-making
- Cross-functional Stakeholder Management
Good-to-have Skills
- Healthcare Technology
- Digital Health Products
- Conversational AI and Generative AI
- Clinical Workflow Design
- Human-in-the-loop AI Systems
- Product Analytics and Experimentation
- Privacy, Safety, and Responsible AI
- Complex Workflow Management
Working Principles
- High Ownership: Take initiatives from ambiguous ideas to successful product launches, with accountability for outcomes.
- Clinical Safety First: Treat user trust, privacy, clarity, and appropriate escalation as core product requirements.
- Collaborative Execution: Work transparently with cross-functional teams and actively incorporate feedback.
- Product Craft: Pay attention to interaction design, communication, usability, and the details that shape user confidence.
- Pragmatic AI: Build reliable, real-world AI experiences with measurable quality, clear limitations, and continuous improvement.