Jobs at Hippocratic AI

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.

Build, deploy, and operate production conversational AI agents for healthcare customers. Responsibilities include designing RAG pipelines, developing tool-calling and MCP integrations with EHRs and enterprise systems, writing production Python, configuring monitoring, executing go-lives, troubleshooting incidents, and serving as a technical customer partner. The role requires approximately 25% travel to customer sites and quarterly travel to Menlo Park.

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.

Lead Hippocratic AI's social media presence across LinkedIn, TikTok, and X: build TikTok from scratch, create executive and brand content, produce short-form video and graphics, manage content calendar and influencers, source stories from cross-functional teams, use AI agents and analytics to optimize performance, and support broader comms and marketing deliverables.

Lead end-to-end deployments of a healthcare AI product for life sciences customers. Conduct onsite workflow discovery, design and configure solutions, drive adoption and ROI, manage stakeholder relationships, train users, measure deployment outcomes, and channel field insights to Product and Engineering to scale deployments.

The LLM Inference Engineer will optimize large language model infrastructure and implement serving architectures, quantization techniques, and latency optimizations. Responsibilities include designing disaggregated serving solutions, benchmarking system performance, and guaranteeing efficient, scalable LLM systems in production.

Lead a regional portfolio of health system partnerships and a team of Directors/senior CS executives. Own executive client relationships, enterprise implementations, change management, and net revenue retention. Build playbooks, drive expansion sales, collaborate with Product/Engineering/Sales, represent the company externally, and support regional hiring and team development. Onsite role in Seattle with occasional travel to Palo Alto.

Drive data-informed decisions through operational reporting, dashboarding, and performance analysis. Split focus on data quality and business reporting, run SQL/Python analyses, build dashboards, produce recurring and ad-hoc reports, and partner with cross-functional GTM and customer teams to surface insights that improve product usage and outcomes.

Serve as technical architect for healthcare AI deployments: scope customer workflows, design and configure agent workflows, define integration architecture, lead project execution, monitor post-launch analytics, and drive continuous optimization while documenting reusable patterns.

Lead as the single executive owner for a flagship life sciences account, manage a CS+FDE pod, drive account strategy, retention, expansion, and implementation, build playbooks and metrics, and partner cross-functionally to align deployments with scientific, operational, and regulatory needs.

Oversee HR operations, compliance, employee experience, and strategic people operations at a growing healthcare AI company. Lead HR initiatives to ensure alignment with business goals and culture during rapid expansion.

The Integration Engineer will design and maintain healthcare data integrations, collaborating with teams to optimize performance and improve reliability using Python and various standards.

The Principal, Strategic Partnerships will lead AI adoption in healthcare by managing executive relationships, discovering use cases, performing economic analysis, and expanding partnerships with major health systems.

Define and document a repeatable inbound AI methodology for healthcare. Partner with 5–7 health systems to design decision trees, IVR logic, provider directory mapping, and escalation rules. Translate workflows into product requirements, influence the Front Door roadmap, and enable deployment teams with playbooks, templates, and training so deployments scale without continuous oversight.

As a Senior Actuary, you will build actuarial models, analyze healthcare data, develop pricing frameworks, and support business development to demonstrate the value of AI in healthcare.

The VP of Enterprise Sales will manage strategic accounts, engaging C-suite executives, architecting deals, and driving software solutions to healthcare providers, while working with various teams to ensure client satisfaction.

Embed with healthcare customers to scope, build, and deploy production-grade conversational AI (RAG, agents, real-time voice) integrated with EHRs and cloud infrastructure, own monitoring and iterative improvements, and feed field insights back into product and research.