Teams at Coursera + Udemy

Own enterprise AI customer deployments from discovery and product scoping through delivery, adoption, and value realization. Translate customer workflows into product requirements, technical solutions, deployment roadmaps, and measurable outcomes. Partner with engineering, sales, customer success, finance, legal, security, and operations while evaluating AI trade-offs, business value, and production readiness. Identify reusable customer needs and help establish scalable product, operating, and deployment playbooks.

Build applied AI systems and prototypes using LLMs, RAG pipelines, vector databases, agentic workflows, structured extraction, and custom models. Design evaluation frameworks, measure accuracy and grounding, analyze errors, and iterate on solutions. Work with large structured and unstructured datasets using Python, SQL, and cloud data platforms. Partner with product, data, engineering, and business teams to translate ambiguous problems into measurable AI solutions and document architectures, prompts, runbooks, and results.

Build and deploy AI-powered customer solutions across discovery, prototyping, and production. Responsibilities include designing secure multi-tenant and hybrid architectures, integrating identity and access management, encryption, networking, data engineering, CI/CD, observability, and production support. The role partners directly with enterprise customers, executive sponsors, and cross-functional teams to solve ambiguous problems, demonstrate prototypes, and standardize successful solutions. Regular domestic and occasional international travel is required.