Head of Engineering

Magical is building an AI-native automation platform for enterprise healthcare.

We believe healthcare organizations will not solve their operational problems by buying another 50 point solutions. They will stand up an agentic workforce: AI agents that can execute real work across fragmented systems, adapt as workflows change, and operate with the reliability, security, and observability healthcare requires.

That is what we are building.

Our work matters. Magical automations have helped identify 200+ positive cancer cases, match suicidal veterans with mental health care, improve care access for patients, and help providers get paid in a $5.2T healthcare system still held together by too much manual work.

We are looking for an AI-native Head of Engineering to help us scale from early customer pull to category-defining execution.

This is not a classic VP Engineering role.

We are not looking for someone whose main value is process, org charts, or big-company operating discipline. We need a deeply technical, product-minded, customer-facing engineering leader who wants to build.

You will own the technical direction of the platform, scale a senior engineering team, partner closely with Product and GTM, and represent Magical in high-stakes conversations with enterprise healthcare executives and technical buyers.

The right person can move from architecture review to roadmap debate to customer escalation to recruiting close without losing altitude.

• Technical direction across our AI platform, reliability, security, observability, and deployment architecture

• The systems that make probabilistic AI reliable enough for enterprise healthcare workflows

• The evolution of the platform so customer deployments become faster, more repeatable, and more scalable

• Engineering quality, speed, ownership, architecture review, incident response, planning, hiring, and performance expectations

• Customer-facing technical credibility across security, reliability, architecture, and product direction

• Hiring and developing exceptional AI-native engineers, product engineers, infrastructure engineers, and technical leaders
  

• Deep technical judgment in LLMs, agents, evals, orchestration, reliability, model behavior, and production AI systems

• A platform builder who thinks in primitives, workflows, observability, governance, developer experience, and repeatability

• Strong product and business judgment around deployment speed, customer trust, scalability, and defensibility

• Customer-facing credibility with enterprise executives and technical buyers

• Experience scaling a high-caliber engineering team through an ambiguous, high-growth stage

• Strong architecture instincts and the ability to earn respect from senior engineers without making every decision yourself

• Fluency in enterprise security and healthcare trust requirements: HIPAA, SOC 2, PHI, permissions, auditability, logs, and data access

• Low ego, high standards, direct communication, and founder-level urgency
  

Agentic automation will not win in healthcare because the demos are impressive.

It will win when the systems are reliable, secure, observable, governed, and economically transformative.

That is the engineering problem.

If we get it right, Magical becomes one of the core platforms healthcare organizations use to deploy AI workers across their most important operational workflows, even when the systems underneath are fragmented, old, and closed.

This is a rare chance to lead engineering at the moment a company moves from early customer pull to category leadership.

This is not the right role for someone who wants to manage from a distance.

We are not looking for:

• A traditional enterprise VP Engineering whose main strength is managing managers

• A big-company operator who wants to add heavy process before the team needs it

• A pure AI researcher who does not want to own production systems, customers, reliability, and business outcomes

• A leader whose experience is limited to legacy automation models and is not excited to build AI-native systems

• A backend-only architect who does not want to spend time with customers, GTM, and enterprise buyers

• A sales-engineering profile who can explain the product but cannot lead architecture, execution, and engineering quality

• A healthcare operator who understands the market but lacks world-class technical depth

We need someone technical enough to earn trust, commercial enough to understand the stakes, and hands-on enough to help the company move faster.