VP of Engineering

Boston / New York City, United States | Posted on 03/31/2026 Industry Pharma/Biotech/Clinical Research Work Experience 10+ years State/Province MA / NY Country United States Job Description VP of Engineering Deliberate AI | Hybrid (NYC or Boston) | Full-Time About the Role Deliberate AI is seeking a VP of Engineering to lead our engineering organization through a pivotal growth phase — from early-stage team to a production-grade platform serving projects across four continents. You'll manage a team of engineers across full-stack, audio-visual data, wearable/mobile sensing, and platform infrastructure, setting the engineering culture, delivery cadence, and technical standards that allow the company to ship reliably under the pressure of clinical milestones and regulatory requirements. This role combines hands-on technical credibility with the organizational judgment to build and retain a world-class team. This is not a “people manager who used to code” role. You'll make meaningful architectural decisions, especially at the boundaries where systems intersect — platform infrastructure, data pipelines, ML integration, and clinical deployment. But your primary impact will be in building an engineering organization that delivers: hiring the right people, removing obstacles, defining how teams plan and ship, and ensuring that the engineering culture reflects our values. We believe a small, sharp engineering team with aggressive use of agentic coding tools — Claude Code, Codex, Cursor, and whatever comes next — can outperform organizations five times our size. You'll be the leader who makes that real: setting the norms for how AI-assisted development works at Deliberate, measuring where it accelerates us, and ensuring it doesn't compromise the reliability bar that clinical software requires. Key Responsibilities Engineering Leadership : Own engineering delivery across all product lines — conversational GenAI assessment agents, passive sensing applications, clinician-facing monitoring dashboards, adaptive intervention systems, and the underlying data and infrastructure layers Team Management : Directly manage Lead Engineers (Full Stack, Audio-Visual Data, Wearables/Mobile Data, Platform) and technical advisors or contractors. Build a culture of technical excellence, psychological safety, and high accountability Hiring & Retention : Lead engineering recruiting in partnership with the CEO — define roles, run interview processes, calibrate offers, and design onboarding. Build the team from its current size to 10+ engineers over the next 18 months Delivery & Execution : Establish engineering planning processes (sprint cadence, milestone tracking, release management) that align with project timelines. You own the question of “will we ship on time, and if not, what's the plan?” Architecture & Technical Direction : Partner with Lead Engineers to make cross-cutting architectural decisions — service boundaries, shared infrastructure, deployment strategy (cloud, on-prem for clinical sites), data architecture, and security posture Platform Strategy : Guide modernization (infrastructure, backend, frontend, mobile, data pipelines) from legacy platform to production-grade clinical deployment infrastructure Clinical Deployment : Work with the clinical operations to ensure engineering supports multi-site, multi-continent deployments with the reliability, monitoring, and incident response that clinical work demands Security & Compliance : Direct the Security, Privacy and Quality Officers to maintain HIPAA and GDPR compliance, implement security best practices, and ensure engineering processes meet 21 CFR Part 11, GCP, and other regulatory requirements Cross-functional Partnership : Collaborate closely with the Product Leads on roadmap prioritization, with the CEO on strategy and resourcing, and with research scientists on ML integration and validation Engineering Culture : Foster an environment of agentic programming, continuous learning, direct feedback, and deep technical craftsmanship. Protect engineering focus while maintaining responsiveness to clinical and business needs Required Qualifications 10+ years of software engineering experience, with 4+ years leading engineering teams (managing managers or tech leads, not just ICs) Proven track record building and scaling engineering teams from 2-5 to 20+ engineers in a high-growth environment Strong technical foundation across full-stack development, cloud infrastructure, and data systems — you don't need to be the deepest expert in every domain, but you need to earn credibility with your leads Experience with cloud-native architectures (GCP / AWS) including containerization (Docker, Kubernetes), CI/CD, and infrastructure-as-code Demonstrated ability to establish engineering processes (planning, delivery, incident response, on-call) without over-bureaucratizing a small team Experience shipping production systems under regulatory or compliance constraints (HIPAA, SOC 2, ISO 27001, or similar) Strong hiring and talent development skills — you've built interview processes, made good hires, and coached engineers into leadership roles Proficiency with agentic programming tools and AI-assisted development workflows Excellent communication skills — you can translate engineering status and tradeoffs for non-technical stakeholders (CEO, clinical partners, board) Bachelor's degree in Computer Science, Engineering, or related field Preferred Qualifications Healthcare or life sciences experience — HIPAA-compliant systems, clinical trial software, medical device software (SaMD), or regulated health tech products Experience with ML/AI product engineering — not necessarily training models, but building the infrastructure and integrations that put models into production Background in mobile application development or IoT/wearable data systems Experience managing engineering in a hybrid team across time zones Familiarity with clinical trial operations , research protocols, or GCP (Good Clinical Practice) — enough to understand the constraints your team ships under Experience with government-funded R&D (NIH, ARPA-H, DoD, NSF) and the milestone-based delivery cadence that comes with it Understanding of audio/video processing pipelines , NLP, or affective computing at an architectural level Publications, conference presentations, or meaningful open-source contributions MBA, MS, or PhD in Computer Science, Engineering, or related field Technical Credibility : You can engage your Lead Engineers on architecture, review system designs, and push back when something isn't right — without micromanaging the implementation Organizational Design : You think clearly about team structure, reporting lines, and how to carve scope as the team grows. You've navigated the transition from “everyone talks to everyone” to “teams with clear ownership” Delivery Focus : You have a bias toward shipping. You know how to break large programs of work into milestones, surface risks early, and keep the team moving without burning people out Recruiting Judgment : You've hired strong engineers and strong leads. You know what good looks like and you're willing to wait for it Clinical Empathy : You take seriously that the systems your team builds touch patient care. Reliability, data integrity, and privacy are non-negotiable engineering requirements, not compliance checkboxes Communication : You translate technical complexity into clear updates for the CEO, clinical partners, and funding agencies. You write well and speak plainly Base Salary : $180,000 - $260,000 (commensurate with experience, qualifications, and location) Equity/stock options with milestone-based vesting Comprehensive health, dental, and vision insurance 401(k) with company match Flexible PTO policy Professional development budget for conferences and training Authorship opportunities on publications describing platform and engineering innovations Conference speaking opportunities About Deliberate AI We're a venture-backed company at the frontier of precision mental health. In partnerships with some of the world's top ranked medical schools and psychiatric hospitals, we've secured non-dilutive funding from the NIH, ARPA-H, DARPA, the FDA and the Wellcome Trust. We're deploying multimodal AI systems in clinical trials and healthcare settings across four continents — and we're hiring the engineering team to build what comes next. Our Values Forge a New Standard of Care — We're not here for incremental. We're here for 10x. Strong Opinions, Open Hands — We speak up because ideas matter more than titles, and we listen because we might be wrong. Bring the Whole Room — The best solutions emerge when the room doesn't think alike. Move Before the Map Is Complete — We ship under uncertainty, course-correct fast, and follow through to the finish. Sharpen Relentlessly — We seek the steepest learning curves and protect focus because sharp people do sharper work. Guard the Patient's Trust — If we wouldn't trust it with our own care, we don't ship it. Location : This is a hybrid role. We work in-person roughly 50% of the time in NYC or Boston — this is how we build culture and solve hard problems together as an early, fast-growing team. Candidates should be based in or willing to relocate to one of these cities. Work authorization : Candidates must be authorized to work in the United States. We welcome applicants who hold US citizenship, permanent residency, or existing work authorization including H-1B (transfer-eligible), OPT/STEM OPT, or TN visa (Canadian and Mexican citizens). If you already hold an H-1B, we will sponsor your green card if desired but we are not currently able to sponsor new H-1B petitions. How to Apply Deliberate AI evaluates candidates based on merit, qualifications, and the skills needed to succeed in the role. #J-18808-Ljbffr