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Head of Product & Technology

Job Description

Head of Product & Technology (CTPO – AI & Product), Miror

Miror is an early-stage, AI-driven health platform focused on women’s health, translating clinical and hormonal health protocols into scalable digital solutions for women in midlife. We are seeking a Head of Product & Technology (CTPO) who will own the end-to-end product vision and roadmap, lead AI-powered product development, and partner closely with a small engineering team to deliver impactful features.

The Role

You will sit at the intersection of healthcare, AI, product, and engineering, defining what we build, why it matters, and in what order. This is a hands-on leadership role for someone who can set strategy for women’s health and AI, while remaining close to discovery, design, and delivery with engineers.

Key responsibilities

Product leadership

  • Own and define the product roadmap aligned with Miror’s vision of holistic menopausal care and long-term health outcomes.
  • Lead discovery to deeply understand user needs across symptoms, lifestyle, mental health, and engagement, especially for women navigating peri/menopause.
  • Translate clinical and hormonal health protocols into user-friendly digital journeys and AI-assisted experiences.
  • Design and iterate on features for symptom tracking and trend analysis, protocol adherence and personalization, community engagement, and integration of supplements, diet, and consultations.
  • Balance short-term MVP execution with long-term platform scalability and data foundations.

AI and technical ownership (product side)

  • Work with the team to select and refine AI approaches (APIs vs custom models, retrieval-augmented generation vs fine-tuning, guardrails, evaluation strategies) aligned with user value, safety, and constraints in a health context.
  • Define user experience patterns for AI, including prompting, input/output flows, user controls, transparency, and safety expectations.
  • Contribute to evaluation and monitoring frameworks for quality, safety, and latency so AI features are reliable, clinically responsible, and privacy aware.
  • Collaborate with engineers as the technical authority on high-level architecture for apps, backend, data pipelines, analytics, and integrations.
  • Make pragmatic build vs buy decisions and manage external vendors or development partners when needed.

Roadmap and prioritization

  • Translate company and user goals into a clear, prioritized 3–6-month roadmap with a strong emphasis on AI-powered experiences.
  • Identify, validate, and prioritize AI use cases such as intake and assessment flows, symptom triage, coaching copilots, personalization, and insight dashboards.

Define analytics requirements and feedback loops to measure impact and enable rapid experimentation and iteration.

Delivery with the engineering team

  • Facilitate product rituals for the engineering team, including backlog grooming, sprint planning, and asynchronous check-ins.

Ensure the team focuses on high-impact problems and that scope supports rapid learning rather than over-building.

Collaborate with engineers to determine sequencing, including what to prioritize for MVP, what to refine, and what to defer.

Communicate complex technical and product concepts clearly to non-technical stakeholders, including the founder and clinical experts.

Healthcare, compliance, and clinical grounding

  • Work closely with medical advisors, doctors, and nutrition experts to ensure clinical credibility in all product and AI experiences.
  • Ensure the product and data architecture align with healthcare regulations and data privacy standards relevant to women’s health.
  • Help establish frameworks for evidence-based recommendations and protocol validation over time.

Ideal candidate profile

Experience

  • 8–10 years in product management, technology leadership, or engineering, with increasing ownership of roadmap, requirements, and delivery.
  • Experience as an AI Product Manager, Technical Product Manager, or similar role working closely with a small engineering team.
  • Proven track record of building and scaling consumer-facing digital products, ideally including at least one AI or large language model-powered product (e.g., chatbot, copilot, personalization system, or workflow automation).
  • Prior experience in healthcare, health tech, wellness, or femtech strongly preferred; experience with health data, behavior change, or regulated environments is a plus.

Skills and competencies

  • Strong product thinking with deep empathy for women navigating peri/menopause and midlife health challenges.

Solid technical foundation: able to read code and architectural diagrams, discuss trade-offs with engineers, and prototype with APIs or LLMs without being the primary individual contributor.

Ability to translate medical and scientific concepts into usable digital experiences and AI-assisted flows.

  • Data-driven mindset, comfortable using analytics and experiments to inform decisions.
  • Comfortable operating in ambiguity and early-stage environments, with a bias toward action and learning.

Engagement details

  • Type: Part-time or contract, with potential for extension or evolution into a longer-term leadership role if there is strong mutual fit
  • Hours: Approximately 15–20 hours per week to start, with flexibility for the right candidate.
  • Duration: Initial 12-week engagement focused on defined outcomes, with the option for ongoing collaboration.
  • Remote position with some overlap required with India or US time zones.

Initial milestone (first 4–6 weeks)

  • Co-create a six-month, AI-focus8-weekduct and technology roadmap for Miror, including clear problem statements, sequencing, and success metrics.
  • Take ownership of one flagship AI feature from concept to launch (for example, a perimenopause assessment or AI coaching companion), including discovery, PRD, user experience flow, and guiding engineers through implementation and launch.
  • Establish foundational product and delivery processes with the engineering team (backlog management, rituals, and metrics) to ensure continuity after the initial engagement.
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