Head of Engineering

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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401(k) match

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

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About this role

Head of Engineering US - Remote, US - Bay Area About Us At Sully.ai , We're Building the Most Impactful Healthcare Company on Earth We believe that access to a great doctor is a basic human right. Today, that's not a reality. Delays, misdiagnoses, administrative chaos, and burnout plague the system. Our Mission One Human, One Doctor . We enable our customers to staff 30% of their workforce with AI by creating a shared agent architecture for scale and efficiency. All powered by our own patented, world-class models and deployed in real-world care. About the Role Sully automates clinical documentation at the point of care. Real-time ambient listening, structured medical notes, and agentic AI workflows that live inside the EHR. We're live in 270+ clinics, have processed 2M+ real physician-patient encounters, and run on custom medical models that outperform GPT, Claude and Gemini on clinical benchmarks. We're not a wrapper company. We're hiring multiple hands on Heads of Engineering to own core product domains: Consultant, Integrations, Mobile, and Platform. Each role has full technical and execution ownership: architecture, roadmap, delivery, and reliability, for its surface area. ─── What You'll Own • End-to-end engineering execution: architecture, roadmap, delivery, reliability • Drive function performance improvements : targeting 50%+ latency cuts across AI inference workflows • Observability, alerting, and model-selection systems that give you real signal at scale • The execution cadence your team needs to stay unblocked: OKRs, standups, backlog ownership, cross-functional alignment • Quality pipelines : for accuracy, completeness, and reliability

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