Senior Vice President of Engineering

Marrow is the platform on which over a million doctors in India prepare for the exams that decide their careers. When a NEET PG aspirant opens the app the night before their exam, our systems have to be fast, correct, and up, there is no second attempt.

We are profitable, fast-growing, and 100% owned by M3 Inc., a Tokyo-listed healthcare leader serving 4 million doctors across 9 countries - which means we build with the ambition of a startup and none of its fundraising risk.

This role owns all of engineering at Marrow. That includes the core platform and the next architecture that takes us from one exam to many and our AI charter, which our board has funded and which you will build largely from scratch.

The raw material is already here: question-level, decision-level data on how a million doctors learn and reason, one of the largest datasets of clinical judgment anywhere. Today it powers how we train doctors in India. Tomorrow, it‘s how we help train machines globally.

We‘re looking for a leader who has done both: owned production platforms at consumer scale, and shipped ML systems that changed user outcomes and who knows which problems belong to which discipline. You‘ll inherit a strong engineering org and a two-person AI nucleus, and you‘ll be judged on what you build from each.

What you‘ll own

• All of engineering at Marrow Backend, Mobile, DevOps, and Data — serving 1M+ doctors at exam-grade reliability
• The re-architecture that takes the platform from one exam to many verticals
• The AI charter: board-funded, currently a two-person nucleus, set the technical agenda, and ship AI-assisted learning deep into the product
• The data platform that turns question-level learning data from a million doctors into the intelligence layer of the product
• The technical vision for Marrow‘s next phase and the org that executes it

What we‘re looking for

• You‘ve owned production systems at consumer scale ,architecture, reliability, performance, cost and not just contributed to them
• You‘ve shipped ML or personalisation systems that changed user outcomes in production, and you know which problems belong to platform and which to ML
• You‘ve built data infrastructure that ML teams actually built on, not data lakes nobody swam in
• You‘ve grown an engineering org meaningfully — hired leaders, not just engineers and can do it again for a new AI team
• Typically 12-15+ years, with hands-on depth in backend and infra; mobile leadership experience is a plus