Product Manager

This role is for one of Weekday’s clients Min Experience: 4+ years Location: Bangalore JobType: full-time 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. 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. 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. 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.