Head of Engineering - AI-Native Healthcare SaaS | Zenara Health

Role

Head of Engineering for an AI-native healthcare SaaS startup. You will be the primary engineering leader reporting to the founder-CEO and will own delivery, personnel, architecture, release engineering, security, AI governance, and recruiting across multiple products.

Key Responsibilities

• Own delivery outcomes across all products: scope management, release schedules, quality controls, and stakeholder alignment.
• Manage the engineering team: hiring, performance evaluations, coaching, feedback, conflict resolution, retention, and culture.
• Define and maintain system architecture across web apps, APIs, infrastructure, and AI integrations; make trade-off decisions and participate in code review and production troubleshooting.
• Design and enforce CI/CD and release engineering practices, environment management, and deployment automation.
• Establish and maintain security posture: access control, secrets management, audit trails, and SDLC security appropriate for healthcare data.
• Define and enforce AI governance policies covering approved tools, IP protection, risk mitigation, and safe AI/ML productization.
• Build and run the recruiting process and engineering organization to scale the company beyond product-stage to commercial-stage.

First 90 Days

• Weeks 1–2: Meet the team, review products and deployments, identify delivery risks and bottlenecks.
• Month 1: Set a regular delivery cadence; define release process, quality standards, and routine engineering communications.
• Months 2–3: Standardize CI/CD across products; implement AI governance; produce an architecture roadmap; begin hiring and create an engineering runbook.

Requirements

• 10–18 years in software engineering, including at least 4 years in engineering management with delivery and personnel responsibility.
• Direct management experience of teams of ~5–20+ engineers (recruitment, performance management, mentorship, and offboarding where necessary).
• Demonstrated system architecture experience across front-end, back-end, database, and infrastructure in SaaS systems.
• Experience building or significantly improving CI/CD pipelines, quality gates, and environment management.
• Managed production cloud infrastructure (Azure or AWS) with awareness of security, reliability, and cost trade-offs.
• Full-stack technical depth sufficient to review code and debug production issues.
• Security fundamentals relevant to healthcare (access control, secrets management, audit trails, SDLC security).
• Strong English communication skills; async-first documentation and decision memos.
• Startup or high-growth experience delivering under ambiguity and tight timelines.

Strongly Preferred

• Experience in healthcare SaaS (EHR, billing, clinical workflows, HIPAA).
• Familiarity with the TypeScript / Node / React ecosystem.
• Understanding of observability and SRE practices (logging, metrics, tracing, incident response).
• Experience productizing AI/ML features safely in production.
• Experience building QA/test automation into engineering culture.
• Leadership of remote-first teams across multiple time zones.

Nice to Have

• Knowledge of FHIR/HL7 healthcare data standards.
• Experience with Kubernetes or container orchestration.
• Familiarity with SOC 2 or similar compliance frameworks.
• Experience in B2B multi-tenant SaaS environments.
• Exposure to mental health / behavioral health domains.
• Familiarity with FDA AI/ML compliance requirements.

Compensation & Benefits (high level)

• Salary range: ₹40–60 LPA plus equity (ESOP).
• Fully remote across India with equipment allowance, comprehensive health insurance, flexible PTO, local (India) holidays, and a leadership development / coaching budget.
• Direct access to the founder-CEO and the opportunity to establish and scale the engineering organization.

Location & Schedule

• Fully remote across India. Role requires 4–8 hours daily overlap with US Pacific Time (PT); leadership availability expected during critical releases or incidents.

Success Criteria

• Predictable and reliable delivery without CEO micromanagement.
• Regular, improving release cadence and enforced quality standards.
• Clear responsibilities, documented architectural decisions, robust security posture, active hiring pipeline, and implemented AI governance enabling safe, fast development.