Own strategic enterprise clients, build executive trust, ensure measurable ROI and adoption, drive expansion, create playbooks, and surface client feedback to influence product roadmap.

Lead technical project delivery by building governance, defining sprint cadence and delivery standards, optimizing CI/CD pipelines, translating technical milestones for stakeholders, and creating repeatable engineering playbooks.

Design scalable systems and playbooks to turn traction into repeatable execution. Partner with product and engineering to translate clinician pain into workflows, shape AI agent behavior to clinical quality standards, and iterate rapidly with customer feedback.

Lead integration strategy and deliver production-ready EHR and partner integrations. Work with customers to gather requirements, collaborate with AI/ML teams to bridge applied GenAI systems, and ship SDKs, proxies, and automation to improve reliability and reusability.

Lead a specific AI Agent product end-to-end: define strategy, guide discovery, design, and delivery; partner with Engineering, Data Science, Sales, and Marketing; translate customer feedback into high-impact features; scale products through rapid experimentation and iteration to drive adoption and measurable healthcare outcomes.

Lead the technical product roadmap for clinical AI products: define goals, metrics, and technical requirements; partner with engineering, ML, and design; document architecture and specs; synthesize customer workflows; make tradeoffs; and ship infrastructure or agentic workflow upgrades improving latency, accuracy, and reliability.

Build and scale core research infrastructure and agentic systems across backend, frontend, and model integrations. Own reliability, observability, and performance; ship research-proven features to production rapidly and develop shared tools and SDKs to accelerate Research, QA, and Engineering.

Own ARR for enterprise healthcare accounts by running high-velocity demos, negotiating and closing contracts, building pipeline at events, partnering with product/engineering, and continuously improving sales process and messaging.

Lead and scale the iOS mobile platform end-to-end: own architecture, roadmap, delivery, and reliability. Drive major performance and crash-rate improvements, build observability and automated testing, coordinate closely with Product/Design/Backend, and improve EHR integrations and technical debt while establishing mobile engineering processes and execution cadence.

Own end-to-end customer delivery for complex B2B SaaS healthcare implementations. Define scope, manage cross-functional teams, mitigate risks, ensure QA and on-time, in-full go-lives, and transition customers to BAU.

Own end-to-end engineering for a product domain, drive large latency improvements, build observability and model-selection systems, lead execution rituals, translate product goals into deliverables, operationalize continuous quality evaluation, and enforce engineering best practices to ensure reliability and scalability.

Lead and scale Sully.ai's multi-cloud platform by owning provisioning, reliability, and automated deployments. Implement GitOps and IaC, standardize developer tooling and CI/CD, optimize scalability and costs for AI workloads, and deliver measurable platform and engineering efficiency improvements.

Own Sully.ai's go-to-market: build and lead the sales engine, own full sales cycle from outbound to close, hire and scale a high-performing sales team, improve demo conversion, and drive predictable revenue growth through enterprise negotiations and a repeatable GTM playbook.

Lead identification and remediation of security and compliance risks, build and run a Third Party Risk Management program, ensure device and contractor environment compliance, automate processes, and support enterprise negotiations to prevent security from blocking customer acquisition.

Design and build end-to-end sourcing infrastructure and automated outbound workflows, ship LLM-powered candidate evaluation and messaging tools, integrate ATS and enrichment data, run weekly sourcing experiments, and close the loop from outreach to hire to achieve scalable, repeatable technical hiring.

Lead strategy, design, and execution of platform integrations connecting Sully.ai's AI clinicians to EHRs and partner APIs. Build and scale the integrations team, ensure HIPAA-compliant, secure, and reliable connectors, ship SDKs and CI/CD/observability standards, and deliver production EHR connectors while partnering with Product, Clinical, Security, and Customer Success.

Design, implement, and optimize core frontend, backend, and model-integration components. Drive engineering direction, ship and scale LLM-powered applications, build robust APIs and streaming systems, establish CI/CD and instrumentation, and deliver production-grade agentic workflows with measurable reliability and performance.

Build and scale a 24/7 global technical support organization for Sully.ai: design ticketing, SLAs, escalation paths and playbooks; manage incidents and EHR integrations; handle complex escalations; collaborate with Product/Engineering to drive improvements and documentation.

Design and build clinical-grade automated evaluation pipelines (LLM-as-judge + human review), define benchmarks, run rigorous experiments, partner with engineering to implement CI gates for accuracy, factuality, and safety, and publish findings to improve model robustness and reduce hallucinations.