Jobs at UpDoc

Build and lead UpDoc’s healthcare compliance program across FDA-regulated software, privacy and security, fraud and abuse, clinical governance, licensure, and federal research. Serve as HIPAA Privacy Officer, manage BAAs and privacy processes, support SOC 2 and HITRUST readiness, oversee reimbursement and clinical compliance, establish policies and training, conduct risk assessments, and report compliance risks to executives and the Board.

Lead end-to-end clinical trial operations from study start-up through closeout. Design and execute decentralized and hybrid trials, manage sites, investigators, CROs, vendors, participant engagement, data collection, documentation, KPIs, risks, and regulatory compliance. Build scalable clinical operations processes and technology workflows while partnering with Clinical, Product, Engineering, Data, Quality, and Regulatory teams to support evidence generation, audits, submissions, and high-quality study execution.

Lead finance as UpDoc’s first in-house finance hire, owning FP&A, financial modeling, budgeting, forecasting, reporting, accounting oversight, grants, revenue cycle management, compliance, fundraising support, and financial systems. Build scalable processes, dashboards, controls, and metrics while partnering with leadership on resource allocation, hiring, strategy, and investor reporting. The role requires hands-on execution in an early-stage healthcare technology startup.

Owns UpDoc’s end-to-end marketing strategy and execution across brand, positioning, content, digital channels, demand generation, communications, events, and sales enablement. The role develops messaging for healthcare and AI audiences, builds awareness and qualified enterprise interest, supports launches and partnerships, manages marketing resources, establishes analytics and processes, and helps build the marketing function at an early-stage digital health startup.

Lead UpDoc’s commercial strategy and go-to-market execution for its AI healthcare platform. Build relationships with health systems and provider organizations, develop enterprise pipeline, manage complex sales cycles, establish pricing and partnerships, convert pilots into scaled deployments, and create commercial operating discipline. Translate clinical and operational outcomes into compelling value propositions while partnering with product, clinical, engineering, and operations teams. Initially operate as a hands-on builder and eventually recruit and lead the commercial organization.

Define clinical reasoning, safety boundaries, evaluation scenarios, datasets, rubrics, and acceptance thresholds for AI-enabled chronic disease products. Analyze failures and edge cases, support clinical validation and outcomes research, interpret clinical and EHR data, and collaborate with Product, Engineering, AI/ML, Data, informatics teams, and clinical stakeholders on integrations and workflows.

Build and maintain patient- and provider-facing applications using SvelteKit, Tailwind, and TypeScript. Develop Android and iOS progressive web applications, extend PWAs with Kotlin and Swift plugins, integrate CGMs and Apple HealthKit, and consume secure APIs. Collaborate with backend engineers, designers, and clinical experts to deliver accessible, reliable, performant, and patient-safe healthcare experiences.

Own AI-powered healthcare products from discovery through launch and iteration. Translate clinical workflows into product requirements, partner with engineering, clinical, and design teams, manage execution, define success metrics, conduct user research, and incorporate AI safely within regulatory and quality requirements. Help shape product strategy and scalable processes in an early-stage startup.

Own the clinical design and product development of AI-enabled chronic disease solutions. Define care pathways, interventions, escalation criteria, safety boundaries, and system behavior. Lead initiatives from problem definition through launch, translate clinical needs into product requirements, review AI conversations and clinical trajectories, identify failure modes, and partner with product, engineering, design, and clinical teams to improve performance and roadmap direction.

Build and own automation systems that eliminate friction across engineering, operations, and compliance. Responsibilities include regulatory workflow automation, CI/CD and developer productivity tooling, AI- and LLM-enabled internal workflows, system integrations, and reliable production software with testing, observability, auditability, and failure handling.

Build and lead UpDoc’s software quality engineering function for regulated, safety-critical healthcare technology. Own risk-based testing, traceability, verification evidence, automated test frameworks, CI/CD integration, defect management, release readiness, and failure investigation across web applications, APIs, integrations, and clinical workflows. Partner with Engineering, Clinical, Product, and Quality/Regulatory teams while establishing scalable quality processes and mentoring a growing team.

Build and maintain reliable integrations between UpDoc and healthcare systems, EHRs, and external APIs. Own integration projects from discovery and architecture through deployment, monitoring, troubleshooting, and maintenance. Develop Python APIs and backend services using FastAPI and Pydantic, implement healthcare interoperability standards, handle failures and data integrity, and create automated tests. Collaborate with healthcare technology stakeholders while supporting security, HIPAA, SOC 2, observability, and clinical reliability requirements.

Build and maintain Python backend services, APIs, healthcare integrations, and reliable platform infrastructure. Collaborate with product, frontend, engineering, and clinical teams to define functionality, ensure safety, troubleshoot production issues, and deliver projects end to end. Contribute to DevOps, CI/CD, observability, testing, code review, and technical architecture for an AI-powered healthcare platform.

Lead development of a patient-facing conversational AI agent for chronic disease management. Build scalable, low-latency voice and multimodal systems, engineer prompts, define evaluation metrics, develop fine-tuning data pipelines, deploy AI models and APIs, assess emerging LLM technologies, and collaborate with clinical experts to validate medical accuracy. Develop backend services using FastAPI and Pydantic while supporting secure, reliable medical AI infrastructure.