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

Role

Zenara Health is hiring a Head of AI to own AI strategy, architecture, and execution across assessment and care/practice products and the AI infrastructure platform. This is a hands-on leadership role focused on production-grade LLM orchestration, clinical NLP, observability, cost management, and building an AI engineering organization that reliably serves clinicians.

Key Responsibilities

• Define the AI roadmap and architecture across products and infrastructure, including model selection and orchestration frameworks.
• Build and lead the AI engineering team (start with one direct report, grow to ~3–4), handling hiring, performance standards, coaching, and culture.
• Design and implement scalable production AI pipelines for LLM orchestration, clinical NLP, and AI-generated clinical insights.
• Establish monitoring, testing, incident response, traceability, and explainability for AI workflows; own pipeline remediation when failures occur.
• Treat AI costs as a production constraint: monitor and optimize per-workflow and per-customer economics (model usage, inference costs, token consumption).
• Create documentation, playbooks, testing standards, and runbooks to convert individual knowledge into repeatable processes.
• Evaluate and integrate new models, frameworks, and orchestration tools to keep clinical AI capabilities current.

First 90 Days

• Weeks 1–2: Audit production AI workflows, pipeline architecture, technical debt, and team dynamics.
• Month 1: Set documentation standards, define testing/monitoring frameworks, and begin tracking AI costs by workflow.
• Months 2–3: Implement monitoring/alerting, develop traceability/logging for decision debugging, start hiring first team member, and make architectural improvements with an evolutionary roadmap.

Requirements

Required

• 8–14 years in software engineering with at least 3 years in leadership of AI/ML teams in industry and demonstrable delivery of AI products to users.
• Extensive, hands-on experience with production-scale LLM orchestration frameworks (examples named in the posting) and production AI pipelines.
• Experience deploying AI in healthcare or regulated sectors and familiarity with compliance challenges.
• Strong architectural mindset focused on scalability, reliability, and cost efficiency.
• Experience with agentic AI workflows and AI-assisted coding pipelines.
• Experience supervising teams of ~2–5+ AI engineers, including hiring and mentoring.
• Excellent written English and an async-first communication style (decision memos, technical designs, risk reports).
• Startup or high-growth company experience.

Strongly preferred

• Healthcare SaaS experience (EHR, billing, clinical workflows, HIPAA).
• Clinical NLP and behavioral health domain knowledge.
• Contributions to published research or open source in ML/NLP (practical industry experience prioritized).
• Experience building AI infrastructure platforms and observability strategies.
• Experience managing AI cost budgets and optimizing inference costs.

Nice to have

• Familiarity with FHIR/HL7, multi-tenant SaaS AI deployments, SOC 2, FDA AI/ML considerations, and mental/behavioral health contexts.

What Success Looks Like

• Production AI systems are reliable and instill confidence in leadership and clinical teams.
• A clear AI roadmap aligned with product strategy and documented architectural decisions.
• Measured AI costs by workflow/customer and optimizations in place.
• Traceability and debugging tools enable teams to investigate AI decisions quickly.
• Active hiring pipeline and a high-performing AI engineering team with clear responsibilities and feedback loops.

Schedule & Location

• Evening IST hours with 4–8 hours daily overlap with US Pacific Time (9am–5pm PT). Flexible schedule proposals are acceptable; leadership presence expected during critical deployments or incidents.

Benefits (summary)

• Specified salary range (see posting) and opportunities for fully remote work within India.
• Equipment allowance, recognition of local Indian holidays, flexible paid time off, and funding for leadership development/coaching.
• Direct communication channels with the CEO and the opportunity to build an AI organization in a clinically relevant domain.