Original job description
AI Engineering Manager
Build the agentic workforce for healthcare
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 build 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 more than 200 positive cancer cases, match suicidal veterans with mental health care, improve access to care, and help providers get paid in a $5.2 trillion healthcare system still held together by too much manual work.
We are looking for a deeply technical, AI-native Engineering Manager to lead a team of up to 12 engineers as we scale from early customer pull toward category-defining execution.
The role
This is not a traditional engineering management role.
We are not looking for someone whose primary contribution is running ceremonies, tracking tickets, or managing from a distance. We need a technical, product-minded leader who can raise the quality and velocity of a team while remaining close to the architecture, the product, and the customer problems we are solving.
You will lead a team responsible for building and operating critical parts of Magical’s AI platform. You will set a high bar for execution, develop engineers, drive technical decisions, and work closely with Product, Design, Deployment, and GTM.
The right person can move from a one-on-one to an architecture review, unblock a production issue, challenge a roadmap decision, and help close an exceptional candidate without losing context or momentum.
What you will own
The performance, development, and effectiveness of a team of up to 12 engineers
Technical execution across a meaningful area of Magical’s AI platform
Engineering quality, delivery speed, ownership, planning, architecture reviews, and incident response
The systems required to make probabilistic AI reliable enough for enterprise healthcare workflows
Clear technical direction within your team, in partnership with senior engineers and engineering leadership
Translating ambiguous product and customer problems into executable technical plans
Improving the platform so customer deployments become faster, more repeatable, and more scalable
Hiring, onboarding, coaching, and retaining exceptional engineers
Creating an environment where engineers have high autonomy, clear accountability, and room to grow
Cross-functional execution with Product, Design, Deployment, Security, and customer-facing teams
What we are looking for
Experience leading a high-performing engineering team through an ambiguous, fast-growing stage
Strong technical judgment in production software systems, architecture, reliability, and operational excellence
Meaningful experience with LLMs, agents, evals, orchestration, model behavior, or other production AI systems
The ability to earn the respect of strong engineers without needing to make every technical decision yourself
Strong product judgment and an instinct for balancing speed, quality, scalability, and customer impact
A track record of developing engineers, addressing performance issues directly, and raising the talent bar
Experience turning broad objectives into clear ownership, technical plans, and measurable outcomes
Comfort operating close to customers and understanding the real-world consequences of engineering decisions
Familiarity with enterprise security and healthcare trust requirements, including HIPAA, SOC 2, PHI, permissions, auditability, logging, and data access
Low ego, high standards, direct communication, and founder-level urgency
Why this matters
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.
As an Engineering Manager at Magical, you will help turn emerging AI capabilities into production systems that healthcare organizations can trust with their most important operational workflows.
You will have the opportunity to shape the team, the technical foundation, and the operating culture during a period of rapid growth.
What this role is not
This is not the right role for someone who wants to manage from a distance.
We are not looking for:
A process-first manager whose primary value is ceremonies, reporting, and administration
A big-company operator who wants to introduce heavy process before the team needs it
A manager who has moved too far away from architecture, technical tradeoffs, and production systems
A pure AI researcher who does not want to own reliability, customers, and business outcomes
A leader who avoids difficult performance conversations or allows standards to drift
A project manager who coordinates work but cannot challenge the technical plan
A backend-only leader who does not want to engage deeply with Product, Deployment, and customer problems
A manager who measures success by output rather than shipped outcomes, system quality, and team growth
We need someone technical enough to earn trust, decisive enough to create clarity, and hands-on enough to help the team move faster.
