Jobs at CertifyOS

Build, test, and deploy production-ready ML services and data workflows on GCP. Implement clean, tested code, CI/CD, and monitoring; create evaluation pipelines and metrics; troubleshoot reliability and latency; and collaborate with product, operations, and engineering stakeholders to deliver end-to-end ML features.

Serve as the primary People partner for India, focusing on Operations: coach leaders, manage employee relations and investigations, improve engagement and retention, support onboarding/payroll/compliance, lead People projects, and drive process improvements across the employee lifecycle.

Lead architecture and implementation of CertifyOS's full‑stack application layer. Define frontend and backend patterns, API contracts, performance boundaries, async UX, AI integration, observability, and engineering practices. Mentor engineers, drive cross‑functional initiatives, and ensure scalable, reliable enterprise B2B product experiences.

Lead and scale CertifyOS's marketing organization to drive predictable pipeline and revenue. Build demand generation across paid, content, SEO, ABM, events, and digital programs; own product marketing, positioning, and launches; establish marketing analytics, attribution, and forecasting; hire and mentor a high-performing team; and partner cross-functionally to align growth, adoption, and retention with company OKRs.

Process and validate provider credentials, licenses, and payor enrollments; research licensure and CME rules; complete applications; communicate with providers and clients; support implementations and draft clear guideline documents.

Own top-of-funnel outbound prospecting for US healthcare payers: map accounts, identify stakeholders, execute multi-channel outreach, qualify opportunities, book and prep high-quality meetings, maintain CRM data and reporting, meet monthly pipeline targets, and collaborate with BD and marketing on messaging and segmentation.

Build and maintain scalable, production-grade systems; own end-to-end feature delivery; influence architecture; improve reliability, performance, and code quality; collaborate with product; participate in on-call and incident response; follow security best practices for sensitive data.

Own the operational lifecycle of cloud-native data infrastructure: design and automate reliable deployments, observability, incident response, SLIs/SLOs, autoscaling and IaC, and improve platform efficiency and data freshness across GKE and Cloud Run.