Role Overview

Sitting at the vital intersection of AI technology, product strategy, and public health systems, the AI Transformation Lead – Health will own the design, deployment, and scale-up of AI-driven health interventions across target geographies in the Global South.

You will serve as the domain-expert bridge between clinical/public health realities on the ground and core machine learning engineering teams. You will be responsible for translating complex public health challenges and live donor funding opportunities into scalable AI product roadmaps, embedding these solutions directly within government health workflows, and driving health portfolio expansion across low- and middle-income country (LMIC) settings.

Key Responsibilities

A. Product Strategy and Ownership

- Define the vision, roadmap, and success metrics for one or more AI-powered health products.
- Translate ambiguous public health problem statements and clinical requirements into clear product strategies, priorities, and functional specs.
- Ensure alignment between AI product goals, ministry objectives, and broader institutional health priorities.
- Continuously refine product direction based on field data, user feedback, and evolving public health needs.

B. End-to-End Product Execution

- Lead the full product lifecycle from field discovery and solution design to deployment and iteration.
- Work daily with engineering and machine learning teams as the core clinical domain expert to build high-quality, practical solutions.
- Drive structured execution through sprint planning, backlog management, and release cycles tailored to low-resource settings.
- Maintain a sharp focus on usability, clinical reliability, and real-world applicability in primary and secondary healthcare environments.

C. AI Solution Deployment and Integration

- Anchor the deployment of AI solutions directly within government health systems and public sector workflows.
- Adapt products to complex local contexts, including infrastructure constraints, user behavior, EMR/CDSS systems, and policy environments.
- Ensure seamless integration with existing digital health platforms and national data architectures.
- Identify and resolve operational and technical bottlenecks affecting successful last-mile deployment.

D. Stakeholder Engagement and Adoption

- Engage directly with ministry of health officials, program managers, and last-mile field staff to drive product adoption.
- Translate complex technical and AI concepts into clear,



actionable insights for non-technical public health stakeholders.
- Build robust, trust-based relationships with health partners, program officers, and local health authorities.
- Systematically capture field feedback to drive continuous product improvement and workflow optimization.

E. Partnerships and Ecosystem Development

- Identify and build strategic relationships with health ecosystem stakeholders across project countries (including Africa and Southeast Asia), spanning governments, multilaterals, foundations, and implementation partners.
- Support strategic partnerships that enable program scale, sustainability, and long-term institutional engagement.
- Contribute to shaping the organization's regional footprint and advisory presence across target health sectors.
- Work with leadership to convert initial high-level exploratory conversations into structured operational opportunities.

F. Grants, Proposals, and Program Development

- Lead and support the development of high-stakes grant proposals, concept notes, and funding applications for global health donors.
- Take live funding proposals (e.g., in high-burden disease areas like AMR or disease surveillance), understand the core clinical problem, and translate it into a compelling, fundable AI use-case narrative.
- Collaborate with partnerships and leadership teams to align proposal concepts directly with donor priorities and practical field execution plans.

G. Portfolio Shaping and Expansion

- Identify the optimal mix of products, rapid pilots, and scaled programs within country health portfolios.
- Balance rapid AI innovation with field-level scalability, cost efficiency, and long-term public system sustainability.
- Contribute to strategic decision-making regarding where to invest, expand, or consolidate health interventions.
- Help build a coherent, high-impact portfolio of AI health interventions aligned with regional disease burdens.

H. Cross-Functional Domain Leadership

- Serve as the central translation layer between technical AI teams (data scientists, ML engineers)



and public health practitioners on the ground.
- Ensure all product and technical decisions are deeply informed by clinical evidence, field realities, and health system capabilities.
- Drive cross-functional alignment across engineers, public health experts, program leads, and government partners toward shared impact goals.

What You Will Own

You will take end-to-end ownership of the health product and program portfolio across target geographies in the Global South—leading initiatives from initial problem framing and donor proposal translation through to large-scale, system-level government deployment.

You will own the operational strategy, solution design quality, last-mile adoption, and portfolio growth for health. Success in this role means taking high-burden clinical challenges, directing technical teams to build intuitive AI tools against those challenges, and successfully embedding those tools into public health workflows so that they are widely adopted, operationally sustainable, and capable of delivering measurable health impact at scale.

Requirements & Qualifications

- Core Public Health Expertise First: 7 to 12 years of overall experience with a strong track record of leading large-scale public health programs (e.g., TB, HIV, Dengue, Malaria, AMR, or tropical/high-burden diseases) with hands-on, last-mile delivery experience in low- and middle-income country (LMIC) settings. (Note: Pure pharma, med-tech, or clinical medicine without public health program execution experience will not fit this role).
- Translational Capabilities: Proven ability to read a live clinical proposal or public health concept note, identify the operational and diagnostic gaps, and conceptualize concrete, buildable AI/ML use cases for technical product teams. (Coding skills are not required, but you must understand AI capabilities well enough to direct technical development).
- Education: Master of Public Health (MPH) or equivalent qualification combined with hands-on program leadership experience is highly preferred. A medical degree (MBBS/MD) is not required.
- Structured Thinking & Grant Writing: Demonstrated ability to write fundable technical narratives, contribute to RFPs/proposals, and bring structure to ambiguous problem statements.
- Travel Expectation: Willingness to travel extensively (up to 40%) to project sites and meet with on-ground teams and ministry officials across countries in Africa and Southeast Asia.

📌 AI Transformation Lead – Health (Delhi)
🏢 Arthan
📍 Delhi