Head of Engineering – Agentic AI Healthcare SaaS

This is a fully remote position, open to applicants in India.

📋 Description

• Delivery Outcomes

• You will manage the delivery across all products, focusing on scope management, release cadence, quality controls, and stakeholder alignment. If delays occur, you will be accountable. Conversely, when a product is successfully shipped, you will receive the recognition for that achievement. Your role will protect engineers from scope adjustments and provide the CEO with reliable delivery timelines, avoiding last-minute emergencies.

• Agentic SDLC & AI Governance (The Differentiator)

• This aspect defines the uniqueness of this position. You will take charge of designing and implementing our agentic software development lifecycle:

• - Human-agent workflow design: Establish how AI agents engage in coding, testing, code review, and documentation, as well as when human engineers must step in.

• - Maker-checker patterns: Create quality checkpoints to address AI inconsistencies. Every AI-generated output will require a human verification step, tailored to its risk level — a UI adjustment necessitates different scrutiny than a database migration.

• - Agent orchestration: Decide which agents to utilize, how to configure them, the guardrails they operate under, and how engineers will oversee their results.

• - AI tool governance: Specify approved tools, intellectual property protection policies, and ensure AI enhances development without introducing risks, particularly concerning clinical/PHI data sensitivity.

• - Continuous refinement: This model is in its infancy. You will assess what is effective, what is failing, and make iterative improvements. The playbook is unwritten — you will create it.

• Engineering Team

• You will have direct oversight of the engineering team, which includes hiring, performance management, coaching, providing feedback, conflict resolution, and retention. The team is small yet impactful; every individual plays a crucial role. You will set the cultural and performance standards. Difficult discussions will happen early. Engineers will want to collaborate with you due to your fairness, directness, and dedication to their development.

• System Architecture

• You will be responsible for the architecture across the entire stack: web applications, APIs, infrastructure, and AI integrations. You will make key decisions regarding trade-offs — speed versus thoroughness, refactor versus ship, infrastructure versus features. You should be capable of reviewing code, debugging production issues, and critically evaluating architectural decisions with depth. In a clinical data context, architectural choices have compliance and safety consequences — you will incorporate those considerations.

• CI/CD and Release Engineering

• You will develop the release pipeline — CI/CD, environments, quality checkpoints, and deployment automation. Unorganized releases will be a thing of the past. You will establish a system that allows the team (and their agents) to deliver confidently and on a consistent schedule.

• Security & Compliance Posture

• You will oversee engineering security, including access controls, secrets management, audit trails, and SDLC security. Handling healthcare data — particularly mental health data — necessitates this focus. You will also ensure that AI-generated code and agent workflows comply with audit and compliance standards. You will enforce rigor without creating bureaucratic obstacles.

• Hiring & Team Building

• You will build the engineering team by defining roles, maintaining hiring standards, conducting technical interviews, and making hiring decisions. You are constructing the organization that will transition the company from startup to scalability. Given our agentic model, you will also need to adopt a unique perspective on team composition: fewer engineers, but of higher caliber, optimized for agent supervision rather than mere code output.

• Your First 90 Days

• **Week 1-2:** Immerse yourself. Meet each engineer one-on-one. Gain an understanding of every product, deployment, and challenge. Map the existing human-agent workflows — identifying what functions well and what is fragile. Pinpoint delivery risks and the most significant bottleneck. Build trust through attentive listening rather than announcements.

• **Month 1:** Establish a regular delivery rhythm. Define the release process and quality benchmarks. Create communication structures (standups, retrospectives, planning). Review current agentic workflows — pinpoint areas where AI output lacks adequate human oversight. Start highlighting risks early and reliably, relieving the CEO of delivery supervision.

• **Month 2-3:** Standardize CI/CD practices across all products. Implement maker-checker quality checkpoints for AI-generated code. Develop the AI governance framework — approved tools, IP protection, and PHI safeguards for agent workflows. Start an architectural assessment with a clear roadmap (not a complete rewrite). Begin recruitment to address gaps. Construct the engineering runbook. Set up feedback and coaching routines.

• **Ongoing:** Take complete ownership of engineering. Deliver reliably. Continuously refine the agentic SDLC. Expand the team. Elevate the performance standards. Instill confidence in the CEO that engineering is in expert hands.

⛳️ Requirements

• First-principles thinker. You approach reasoning from foundational concepts rather than relying solely on past experiences. When faced with unprecedented challenges — such as designing quality gates for agent-generated clinical software — you find solutions.

• High learning velocity. The agentic SDLC represents uncharted territory. You may not have previous experience in this specific area, but you learn rapidly enough that it becomes irrelevant. You have repeatedly transitioned into unfamiliar domains and achieved effectiveness promptly.

• Ownership-oriented. You perceive engineering leadership as ownership of outcomes rather than merely managing tasks. You step into chaotic delivery environments and impose order through clarity and accountability, avoiding excessive processes.

• Startup-proven. Your background includes experience in startups, not solely large enterprises. You have successfully delivered real products to actual users under genuine deadlines. You understand the distinction between building something and delivering it.

• Technically credible. You possess the ability to write and review code, debug production issues, and comprehend systems architecture at scale.

• Direct and fair. You provide constructive feedback that fosters engineer development. You manage conflicts promptly. Your teams trust you because you are honest, consistent, and keep them focused.

• Raw intellect is non-negotiable. This role necessitates someone who can navigate uncharted territory — designing human-agent engineering workflows, making architectural decisions with clinical data constraints, and developing an engineering organizational model that lacks a pre-established playbook. We place significant weight on intellectual capacity.

• Strong academic foundations from a rigorous technical program (IIT, NIT, BITS, or an equivalent program). We value the problem-solving skills these programs foster.

• Experience in building and leading engineering teams (5-15 individuals) at startups or high-growth companies. You have shipped SaaS products, not merely maintained them.

• Familiarity with or a strong interest in agentic AI workflows — utilizing AI agents in the development process, not merely as autocomplete. If you have previously experimented with agent-driven development, that is a considerable advantage.

• Healthcare/healthtech experience is highly preferred — particularly regarding compliance, PHI management, or clinical workflows. While not mandatory, it will accelerate your acclimatization.

• You have thoughtfully considered AI governance in engineering — including IP, security, quality, and auditing — and possess well-formed opinions rather than just questions.

🏝️ Benefits

• Competitive salary and equity options.

• Flexible working hours and the opportunity for remote work.

• Comprehensive health benefits, including dental and vision coverage.

• Professional development opportunities and a culture of continuous learning.

• Supportive and inclusive work environment.