Teams at Coursera + Udemy

Build and deploy AI-powered solutions for enterprise and campus customers. Scope customer environments, prototype agentic AI solutions, design secure multi-tenant and hybrid architectures, and productionize validated solutions. Responsibilities include backend engineering, cloud infrastructure, data engineering, IAM, encryption, secure networking, CI/CD, observability, and production support. The role is highly customer-facing, involving executive discovery, live demonstrations, go-live support, and regular domestic and occasional international travel.

Lead backend engineering initiatives for the Monetization team by designing scalable microservices, APIs, storage layers, and data models. Build and monitor services, conduct A/B testing, analyze metrics, and use insights to guide product decisions. Collaborate with product managers and stakeholders on requirements, technical tradeoffs, architecture, and roadmap priorities while contributing hands-on development and technical leadership.

Build and improve test infrastructure, automation frameworks, CI/CD pipelines, and end-to-end testing strategies. Lead quality initiatives, develop AI-augmented testing solutions, monitor test environments, support incident resolution, and use quality and performance metrics to improve software reliability. Collaborate with Infrastructure, SRE, engineering leaders, and product teams in an agile environment to expand test coverage and enable safe, efficient delivery.