Jobs at Hippocratic AI

Own the payor and provider vertical product strategy, identifying high-value healthcare workflows and translating customer, regulatory, clinical, and operational needs into roadmap priorities. Partner with customers, Engineering, clinical safety, Sales, and Marketing to define ROI, ship safe AI voice solutions, and transition use cases from pilot to production. Build value propositions, ROI models, and case studies while driving adoption and expansion.

Leads enterprise growth marketing, ABM, digital acquisition, marketing operations, MarTech, revenue attribution, analytics, and budget strategy. Owns demand generation, marketing data architecture, lead routing, CRM integration, conversion optimization, executive reporting, and AI-enabled targeting and automation. Partners with Sales, RevOps, Legal, Security, Compliance, and Customer Success to generate qualified healthcare enterprise pipeline and improve revenue impact.

Build and scale AI-powered healthcare voice-agent SaaS products across front-end and back-end systems. Develop APIs, dashboards, mobile applications, reusable frameworks, and secure user experiences using TypeScript, React, Python, and cloud technologies. Collaborate with AI researchers, product managers, designers, and healthcare professionals; conduct code reviews, mentor engineers, resolve technical bottlenecks, and support agile continuous delivery.

Own product positioning, messaging, and go-to-market strategy for enterprise agentic AI products in healthcare. Lead launches, develop sales enablement and customer-facing content, build buyer personas, monitor market intelligence, and translate complex AI capabilities into credible business value. Partner cross-functionally with Product, Sales, Customer Success, Legal, and Compliance while ensuring messaging meets clinical, regulatory, and brand standards.

Build and maintain scalable backend infrastructure for healthcare AI applications. Develop distributed multimodal data pipelines, APIs, microservices, data ingestion and metadata systems, and ML enablement workflows. Optimize performance, reliability, monitoring, and uptime for production LLM systems. Collaborate with data scientists, ML engineers, physicians, and product managers to translate healthcare requirements into technical solutions. This is an in-person role five days per week in Menlo Park.

Lead full-cycle recruiting for technical, sales, and engineering roles in a high-growth healthcare AI company. Build structured interview processes, assess candidates rigorously, close senior talent, improve recruiting efficiency, track hiring metrics, and partner strategically with hiring managers. The role also involves developing recruiting infrastructure, supporting compensation and offers, and hiring within AI, healthcare, and potentially regulated environments.

Owns post-go-live relationships with health system customers, driving retention, adoption, measurable clinical and operational outcomes, executive business reviews, risk forecasting, and expansion into additional use cases. The role manages a named account portfolio, builds ROI cases, supports workflow change, and partners with Sales on commercial growth. It requires executive engagement with clinical, operational, and financial leaders and includes 25–40% travel.

Owns healthcare AI deployments from workflow discovery and solution design through configuration, integration, launch, adoption, and measurable impact. Maps clinical and operational workflows, determines automation opportunities, configures and tests agents using JSON, command-line tools, and version control, validates data, coordinates security and go-live activities, and builds impact dashboards. Partners with healthcare customers, executives, engineers, product managers, and clinical experts while managing complex technical and operational dependencies.

Build reliable training, evaluation, deployment, and data-feedback pipelines for a recursively self-improving machine learning system. Design reward and feedback signals, mitigate reward hacking and distribution drift, develop evaluation harnesses, debug model regressions, stabilize non-stationary learning loops, and ship production ML systems. The role requires strong Python and machine learning engineering fundamentals, reinforcement learning knowledge, production experience, and familiarity with feedback-driven systems such as RLHF, RLAIF, active learning, or agent evaluation.

Build tailored demos and prototypes for an agentic AI platform, write code and integrations, configure agent workflows, and lead technical narratives during enterprise sales cycles. Conduct discovery, design solutions, present to clinical and business stakeholders, support pilots, and communicate field insights to Product and ML teams. The role requires strong coding, consulting, presentation, storytelling, and client-facing skills in a full-time Menlo Park office environment.

Establish and lead a scalable Quality Management System for AI-enabled life sciences products. Own CAPA, deviations, change control, document control, training, risk management, supplier quality, audits, inspections, and quality metrics. Partner with Product, Engineering, Clinical, Regulatory, Security, and Medical Affairs teams to embed quality-by-design, validate AI and software systems, manage vendor qualification, and maintain inspection readiness. Build and mentor the quality organization while advising executives on compliance and risk.

Develop and deploy autonomous clinical conversation workflows, including prompt engineering, conversation logic, safety guardrails, and integrations with EHRs, scheduling systems, and telephony platforms. Analyze model outputs and user outcomes, collaborate with clinicians and engineering teams, maintain production code, and support customer go-lives. The role begins as a residency program and may progress into Forward Deployed Engineering, Engineering, or Product.

Leads the strategy, design, execution, and measurement of B2B events and executive experiences. Builds an integrated events calendar, connects programs to pipeline and revenue, develops account-based marketing personalization, manages budgets and vendors, and leads a lean team. The role oversees conferences, trade shows, executive dinners, roundtables, and Customer Advisory Boards while using AI agents and automation to scale engagement, follow-up, and event impact. Regular travel of 25% to 40% is expected.

Lead Hippocratic AI’s federal public-sector growth practice, focusing on VA and HHS relationships, partner development, opportunity qualification, capture strategy, proposal development, and account management. Build a qualified pipeline, develop teaming and pricing strategies, coordinate compliance and technical inputs, and establish GovCon infrastructure for a new vertical. The role requires close collaboration with government stakeholders, prime contractors, channel partners, and internal teams while translating healthcare AI capabilities into compelling federal value propositions.

Design and operate a GPU management and scheduling platform for approximately 30 AI models across heterogeneous hardware. Build metrics pipelines, admission control, autoscaling, cloud orchestration, infrastructure automation, deployment pipelines, and monitoring systems. Develop production software in Python and Go, operate secure fault-tolerant cloud infrastructure, enforce healthcare security and compliance policies, troubleshoot complex issues, and mentor engineers.

Lead product analytics for healthcare AI products by defining success metrics, evaluating product and program impact, building ROI and financial models, improving instrumentation, and translating complex analyses into recommendations for product strategy and roadmap decisions. The role partners with product, engineering, clinical, customer success, executives, and customers, presenting insights on adoption, operational efficiency, costs, capacity, and patient outcomes.

Lead end-to-end post-training for LLMs using reinforcement learning and on-policy distillation to improve clinical reasoning, safety, and alignment. Design RL/OPD methods, build reward models and verifiers, create healthcare conversational environments with synthetic data, automate post-training loops, run experiments, and collaborate with research, engineering, and clinical teams to deploy models at scale.

Lead AI deployments for payor customers from planning through launch and adoption. Coordinate cross-functional teams, manage timelines, risks, training, stakeholder alignment, and implementation readiness. Translate payor workflows and business priorities into actionable plans, resolve blockers, guide organizational change, and develop repeatable deployment playbooks. The role requires regular customer travel and close collaboration with product, engineering, implementation, customer success, and clinical teams.

Leads regional customer success for health system partnerships, managing Directors and senior Customer Success Executives. Owns executive relationships, enterprise implementations, clinical workflow integration, customer success metrics, retention and expansion sales. Builds scalable onboarding, training, change-management playbooks and operating frameworks while partnering with Product, Engineering, Clinical, and Sales teams to improve adoption, operational efficiency, patient outcomes, and net revenue retention.

As a Senior Staff AI Engineer, define multi-year technical strategy, architect platforms for voice-based AI in healthcare, mentor engineers, and represent the company in external discussions.