Senior Engineer, MetaGO Health Location: Mumbai (hybrid) · Experience: 4–6 years · Reports to: CTO · Type: Full-time About MetaGO Health MetaGO Health runs medically supervised GLP-1 and weight-management programs in India. We combine doctors, coaches, medicine delivery and daily patient engagement in one platform. Our engineering team is small, senior-leaning, and builds with AI agents as part of everyday work. The role You will design and ship the core systems behind our care programs, and set the standard for how our team builds with AI. You decide where AI speeds us up and where a human must own every line. You will turn one-off builds into shared platform capabilities other teams reuse. What you will do • Own architecture across the platform: care dashboards, medicine operations, payments, sales tooling and patient engagement. • Define clear service boundaries and data ownership between these domains, integrated through APIs and events, not shared databases. • Own payment integrations: gateways, recurring payments, refunds, webhooks and reconciliation. • Build sales and pre-sales systems: lead routing, CRM and telephony integrations, AI-assisted sales workflows. • Build and harden shared platform pieces: auth and RBAC, audit logging, event processing, notifications, and a model-agnostic LLM layer. • Ship production AI workflows with prompt versioning, evals, cost and latency tracking. • Use AI coding agents daily: write specs, break work into agent-sized tasks, review and own the output; maintain the team's AI coding standards and guardrails. • Design relational schemas with row-level security, indexes, migrations and rollback plans; make every service observable. • Design data flows so every domain lands cleanly in our central data warehouse for reporting and AI. • Review code from engineers and AI agents alike, and mentor junior engineers. • Build security, privacy and compliance controls into the systems you own. Must-haves • 4+ years building backend or full-stack production systems; 2+ years owning architecture decisions. • Strong TypeScript / Node.js; solid React or a similar frontend framework. • Deep SQL and relational database design: schema design, query plans, indexing, migrations. • Event-driven design with message queues: idempotency, retries, replay. • Shipped at least one LLM feature to production, with evals and cost controls, not just a demo. • Daily, hands-on use of AI coding agents, and a clear view on where they fail. • Security fundamentals, secrets management, encryption, input validation, least privilege. • Experience running services on a major cloud provider. Nice-to-haves • Health-tech, fintech or other regulated-domain experience. • Agent frameworks and LLM observability tooling. • Payment gateway, CRM, telephony or messaging-platform integrations. • Ai & AWS Cloud Certificates