Director/Sr. Director Engineering- Clinical AI + Care Delivery

About the role

Midi Health is transforming healthcare for women in midlife, delivering expert, personalized care through a virtual-first platform built around the needs of women in perimenopause and menopause. Technology is central not only to the patient experience, but to how our clinicians deliver exceptional care at scale. We believe AI will fundamentally reshape care delivery — reducing administrative burden, improving clinical workflows, and giving providers better tools to focus their time where it matters most: with patients.

The Clinical Director of Engineering, Clinical AI & Care Delivery will lead the engineering teams behind the systems and tools that power Midi’s clinicians, medical assistants, and care workflows. This is a true player‑coach role at the intersection of AI, healthcare, and software engineering.

Responsibilities

• Lead the engineering roadmap and execution for Midi’s clinician‑facing tools, care delivery systems, clinical workflows, and AI‑powered automation.
• Identify opportunities to use AI and agentic systems to automate workflows, augment clinicians, and improve the efficiency and quality of care delivery.
• Build and lead high‑performing engineering teams with a culture of ownership, accountability, speed, and high technical standards.
• Stay hands‑on through architecture decisions, code reviews, prototyping, and AI‑assisted development.
• Partner closely with Product, Clinical, Operations, and Data Science to translate complex care delivery problems into scalable technical solutions.
• Drive engineering quality, velocity, reliability, and operational health across your area.
• Hire, mentor, and develop engineers and engineering leaders as the organization grows.
• Collaborate with engineering leaders across Midi on architecture, technical strategy, and company‑wide engineering priorities.
• Help define how Midi uses AI and modern development tools to fundamentally rethink how healthcare is delivered.

Requirements

• Deep software engineering foundation – meaningful time as a senior individual contributor building sophisticated applications and systems.
• Proven engineering leadership – 5+ years of engineering management experience and have led organizations of 10+ engineers.
• Player‑coach mindset – comfortable operating at the leadership level while remaining technically credible and close enough to the work to help the team make better decisions.
• Applied AI experience – recently used AI coding agents or AI/LLM technologies to build something meaningful and have a practical understanding of what these technologies can — and cannot — do.
• Strong systems thinking – able to take complex, multi‑step human workflows and think creatively about how technology and AI can make them dramatically better.
• Executive‑level communication and judgment – able to confidently partner with senior technical, clinical, and operational leaders and communicate complex trade‑offs clearly.
• Exceptional cross‑functional instincts – naturally build trust with stakeholders who may approach problems very differently from an engineer.
• First‑principles thinking – ask the right questions, communicate clearly, and align early rather than building in isolation.
• Strong ownership mindset – close loops, take accountability for outcomes, and step into problems rather than waiting for someone else to solve them.

Skills

• Experience with AI/ML engineering, LLM‑powered products, agentic systems, or workflow automation.
• Experience building internal tools or software for complex operational users.
• Experience with Python, Django, React, and AWS.
• Experience in healthcare or another highly regulated environment.
• Familiarity with EHRs such as Athenahealth, clinical workflows, or HIPAA‑regulated systems.
• Experience building AI products where accuracy, reliability, human oversight, and trust are critical.

Benefits

• Wide range of benefits and equity in the company.

Pay

The estimated salary range for this role is $250,000‑325,000 per year, based on factors such as experience and skills.

Schedule

Hybrid – 2 days/week in the San Francisco or Palo Alto office (San Francisco Bay Area).