Head of Engineering

About the opportunity

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Head of Engineering - AI-Native Healthcare SaaS | Zenara Health based in India. This is a high-impact engineering leadership role at the intersection of AI, SaaS, and healthcare technology. You will take ownership of engineering outcomes across multiple products, from architecture and delivery to security and compliance. A defining part of the role is designing and continuously improving an AI-native software development lifecycle where human engineers work alongside AI agents. You will establish quality gates, governance practices, and escalation mechanisms that enable rapid development without compromising reliability or safety. Working directly with the Founder-CEO, you will shape engineering strategy, culture, architecture, and team growth. The role is ideal for a technically credible startup leader who thrives in ambiguity and approaches unfamiliar problems with first-principles thinking. You will have the opportunity to build a high-caliber, high-leverage engineering organization designed for the next generation of software development. Accountabilities: Own engineering delivery across all products, including scope management, release cadence, quality standards, stakeholder alignment, and predictable execution. Design and continuously refine the human-agent software development lifecycle, defining how AI agents participate in coding, testing, code review, documentation, and other engineering activities. Establish maker-checker workflows and risk-calibrated quality gates to ensure AI-generated software and technical artifacts receive appropriate human verification. Define agent orchestration practices, including agent selection, configuration, supervision models, guardrails, and escalation protocols. Establish AI tool governance covering approved tools, intellectual property protection, security, quality, auditability, and safeguards for sensitive healthcare data. Measure the effectiveness of agentic engineering workflows, identify weaknesses, and continuously improve the operating model. Directly manage and develop the engineering team, including hiring, performance management, coaching, feedback, conflict resolution, and retention. Own full-stack system architecture spanning web applications, APIs, infrastructure, and AI integrations, making informed trade-offs between speed, quality, scalability, and technical debt. Review code, troubleshoot production issues, and provide technically substantive input on architectural and engineering decisions. Build and standardize CI/CD pipelines, environments, deployment automation, release processes, and engineering quality checkpoints. Own engineering security practices, including access controls, secrets management, audit trails, secure development processes, and controls for AI-generated code and agent workflows. Build the engineering organization for scale by defining roles, maintaining high hiring standards, conducting technical interviews, and shaping team composition around effective human-agent collaboration. Establish delivery rhythms, engineering standards, documentation, runbooks, feedback mechanisms, and operating processes that create clarity without unnecessary bureaucracy. During the first 90 days, assess products and engineering workflows, establish delivery cadence, strengthen quality controls, standardize CI/CD, implement AI governance, assess architecture, identify hiring needs, and establish a sustainable engineering operating model. Requirements: Demonstrated ability to reason from first principles and solve complex, unfamiliar problems where established playbooks may not exist. Strong academic foundation from a rigorous technical program such as IIT, NIT, BITS, or a demonstrably equivalent institution. Proven experience building and leading engineering teams of approximately 5–15 people within startups or high-growth environments. Track record of building and shipping SaaS products used by real customers, rather than primarily maintaining existing systems. Strong technical credibility, including the ability to write and review code, debug production issues, understand system architecture, and make informed engineering trade-offs. Familiarity with or strong interest in agentic AI development workflows, particularly the use of AI agents beyond conventional coding-assistant or autocomplete functionality. Strong understanding of how AI can participate in software development while remaining subject to appropriate human oversight, quality controls, and governance. Demonstrated interest in AI governance covering security, intellectual property, quality, auditability, and responsible use of AI in engineering. Healthcare or healthtech experience is strongly preferred, particularly exposure to compliance requirements, protected health information (PHI), sensitive data, or clinical workflows. Experience with CI/CD, release engineering, software quality practices, infrastructure, security, and scalable architecture. Strong ownership mindset, with a focus on measurable outcomes rather than task administration or status reporting. High learning velocity and the ability to become effective quickly in unfamiliar technical or business domains. Direct, fair, and constructive leadership style, with strong coaching, communication, conflict-resolution, and stakeholder-management skills. Comfort operating in a startup environment characterized by ambiguity, rapid change, high accountability, and significant individual impact. Availability for approximately 6 hours of working-time overlap with US Pacific Time. Benefits: Compensation positioned well above typical Indian startup market levels for comparable engineering leadership roles. Fully remote work opportunity across India. Equipment allowance. Comprehensive health insurance. Culturally recognized local holidays in India. Flexible paid time off. Dedicated budget for leadership development and coaching. Direct and regular access to the Founder-CEO without unnecessary management layers. Opportunity to shape engineering strategy, culture, architecture, and team structure from an early stage. Opportunity to build and operationalize an AI-native engineering organization and help define a new model for software development. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Qualifications

• : Demonstrated ability to reason from first principles and solve complex, unfamiliar problems where established playbooks may not exist.
• Strong academic foundation from a rigorous technical program such as IIT, NIT, BITS, or a demonstrably equivalent institution.
• Proven experience building and leading engineering teams of approximately 5–15 people within startups or high-growth environments.
• Track record of building and shipping SaaS products used by real customers, rather than primarily maintaining existing systems.
• Strong technical credibility, including the ability to write and review code, debug production issues, understand system architecture, and make informed engineering trade-offs.
• Familiarity with or strong interest in agentic AI development workflows, particularly the use of AI agents beyond conventional coding-assistant or autocomplete functionality.
• Strong understanding of how AI can participate in software development while remaining subject to appropriate human oversight, quality controls, and governance.
• Demonstrated interest in AI governance covering security, intellectual property, quality, auditability, and responsible use of AI in engineering.