Head of Engineering

Stealth Startup; Boston (MA); In loco; USD 220.000 - 320.000; Tempo pieno

Descrizione del lavoro

Stealth Startup in Boston is looking for a Head of Engineering to lead AI and healthcare technology platforms. You will own AI model strategy, deployment, and cost optimization, shipping production-ready software for a multi-tenant healthcare platform.

You will build evaluation frameworks, empower engineers, and drive reliability and security, including HIPAA compliance and auditability. Collaboration with clinical stakeholders is essential to translate requirements into scalable, robust

Competenze

• 7+ years of experience building and owning production systems, including leadership.
• Hands-on experience with Large Language Models (LLMs) in production and post-launch challenges.
• Awareness of the latest AI developments and evaluating new models.
• AI-first engineering practices and use of AI coding tools.
• Experience making architectural decisions that scale with AI evolution.
• Strong software engineering fundamentals for large-scale systems.
• Ability to work autonomously in fast-moving environments.
• Experience joining an existing team and raising standards.

Mansioni

• Own end-to-end R&D delivery, translating customer needs into production-ready software.
• Standardize phone system integrations to onboard medical practices efficiently.
• Maintain high data integrity across EHRs, telephony, and third-party APIs.
• Understand and optimize the total cost of product delivery, including telephony and AI usage.
• Improve system reliability via observability, alerts, and incident response.
• Embed security/compliance (HIPAA) into platform by default.
• Define technical direction and align engineering priorities.
• Hire and mentor engineers, fostering AI-driven, high-quality work.
• Collaborate with clinical/product stakeholders to translate requirements into scalable solutions.

Conoscenze

LLM experience

AI-first engineering

Architectural design

Team leadership

Autonomy

Code reviews

Production systems

Descrizione del lavoro

Head of Engineering – AI & Healthcare Technology

What You'll Own

• Own how the company uses AI models, including model selection, deployment, and cost optimization. Continuously improve the product as models evolve, using less expensive models where they meet the required quality standards.
• Build evaluation frameworks and quality feedback loops to demonstrate, with evidence, whether documentation is accurate, complete, and consistent, and whether new capabilities are ready for real-world clinical practices.
• Empower engineers and non-engineers to build and ship products using the best available AI models and development tools. Continuously improve team workflows as these tools advance, while maintaining high standards for the quality and security of customer-facing releases.

Systems and Delivery

• Own end-to-end R&D delivery, translating ambiguous customer needs into reliable, production-ready software for a growing multi-tenant healthcare platform.
• Standardize phone system integrations to make onboarding new medical practices faster, more efficient, and repeatable.
• Maintain exceptionally high standards for correctness and data integrity across integrations with Electronic Health Records (EHRs), telephony systems, and third-party APIs.
• Understand and optimize the complete cost of product delivery, including telephony, transcription, and AI model usage, while designing for sustainable unit economics.

Reliability and Security

• Improve system reliability through robust observability, alerting, incident response processes, and deployment pipelines.
• Build security and compliance into the platform by default, including HIPAA compliance, encryption, and auditability, and establish standards for the engineering team to follow.

Technical Leadership

• Define the team's technical direction and build alignment around architectural decisions and engineering priorities.
• Hire exceptional engineers who raise the bar and foster a culture that combines AI-driven ambition with rigorous quality standards.
• Improve engineering capabilities through code reviews, design discussions, and collaborative programming.
• Partner with clinical and product stakeholders to translate requirements into sound, scalable technical solutions.

Customer Empathy and Product Excellence

• Understand how nurses, healthcare providers, and practice staff rely on the platform in their daily workflows. Identify gaps, prioritize improvements, and ensure solutions are delivered effectively.
• Pay close attention to user experience details, including presenting information more clearly, reducing unnecessary clicks, and making the next action intuitive.
• Represent the customer's perspective within the engineering organization, ensuring the team remains focused on the people and workflows the product serves.

What Good Looks Like

• You bring energy and urgency to the work, helping the team tackle meaningful and challenging problems every day.
• Each new generation of AI models improves the product, and adopting new models becomes a routine process rather than requiring a major rebuild.
• Product documentation quality is measured with evidence, and new capabilities reach customers only after meeting established quality standards.
• A small engineering team delivers an exceptional amount of work because AI is embedded throughout its development processes.
• New medical practices are onboarded through standardized, repeatable integrations, allowing the platform to scale across more practices and enterprise customers without compromising reliability or security.
• The cost of delivering the product decreases as usage grows.
• Engineers continuously improve through your feedback, standards, and established engineering practices, while new hires further strengthen the team.
• The CEO and the wider team trust you to make critical technical decisions, allowing others to focus on their respective priorities.

What We're Looking For

Must Have

• 7+ years of experience building and owning production systems, including experience hiring and leading engineering teams.
• Hands-on experience building with Large Language Models (LLMs), not just building infrastructure around them. You have shipped LLM-powered features to production and managed post-launch challenges such as evaluation, quality drift, latency, and cost.
• Strong awareness of the latest AI developments. You actively experiment with new models and agentic tools, have a clear perspective on their future direction, and can distinguish genuine technological breakthroughs from hype.
• AI-first engineering practices. You use AI coding tools and agents daily and have transformed how a team works through improved workflows, tooling, code reviews, and task ownership.
• Experience making architectural decisions that hold up under real-world conditions and designing systems that improve as AI models evolve, without requiring a complete rebuild with every release.
• Exceptional software engineering fundamentals and experience designing large-scale systems, combined with a strong understanding of how AI changes team responsibilities and software development practices.
• Ability to work autonomously in fast-moving, ambiguous environments while bringing clarity, alignment, and momentum to the wider team.
• Experience joining an existing team and codebase, earning credibility with established engineers, and raising standards through influence, practical contributions, and effective processes.

Strong Signals

• Experience in healthcare, fintech, or other regulated industries, with familiarity with compliance requirements such as HIPAA, encryption, and auditability.
• Experience with real-time voice systems, including telephony, streaming audio, speech-to-text, or WebSockets.
• Experience building integrations with EHRs or other complex third-party systems and making those integrations standardized and repeatable.

Who This Role Is Not For

• You prefer managing from a distance and leaving architecture, development processes, and the quality of customer-facing releases to others.
• You measure success by the number of people reporting to you.
• You expect a fully researched Product Requirements Document (PRD) for every change rather than taking ownership of a problem and driving it forward.
• You view AI as just another roadmap feature or prefer waiting for tools and best practices to stabilize before adopting them.
• You are excited about the newest AI models but not about the work required to make them reliable for clinicians during live calls.
• You want to focus exclusively on technical challenges while leaving customer problems and pain points to others.

Compensation

• Base Salary: Competitive compensation for a seed-stage healthcare technology company.
• Equity: Early-stage equity grant, offering the opportunity to join early and help build the engineering organization from the ground up.