At a glance
- Experience
- 8+ years experience
- Location
- India
About Coursera
- Coursera and Udemy are now one company, bringing together two mission-driven brands to create the world’s most powerful platform for turning learning into progress. Together, we help more than 300 million learners and 12,000+ enterprise customers build the skills they need for a world being reshaped by AI. Read more about the combined company by visiting our blog.
About the role
- We are looking for a Senior Product Manager, Applied AI to own customer deployments from initial discovery and product scoping through delivery, adoption, and value realization.
- In this role, you will work directly with enterprise customers to understand their most important workflows, translate business objectives into clear product and technical requirements, and build a sequenced deployment roadmap.
- This is an opportunity to join an emerging motion at an early stage and requires people with entrepreneurial mindset.
Responsibilities
- Build trusted relationships with customer executives, business leaders, technical stakeholders, and end users.
- Lead discovery to understand customer objectives, workflows, user needs, data and technical constraints, and desired business outcomes.
- Identify and prioritize high-value use cases, define the minimum viable deployment, and establish clear success and acceptance criteria.
- Translate ambiguous customer problems into clear product requirements, prioritization decisions, and a sequenced product and deployment roadmap.
- Create high-quality product artifacts, including problem statements, product requirements, workflow definitions, user stories, acceptance criteria, prioritization frameworks, and executive decision documents.
- Own delivery governance across Coursera and customer teams, maintaining clarity on scope, timelines, responsibilities, risks, and unresolved decisions.
- Work closely with Forward Deployed Engineers and internal Engineering teams to translate business workflows into deployable technical solutions.
- Define the value hypothesis for each customer engagement and establish the business, adoption, and product metrics required to measure success.
- Identify recurring customer workflows, requirements, and technical patterns that can become reusable product capabilities.
- Partner with Product and Engineering teams to bring field insights into the broader roadmap and build repeatable discovery, scoping, deployment, and measurement playbooks.
Requirements
- 8+ years of relevant experience across B2B product management, enterprise software, technical consulting, solutions delivery, or related roles, with clear ownership of product or customer outcomes.
- Demonstrated experience taking technically complex enterprise products, platforms, or customer deployments from discovery and scoping through production launch and adoption.
- Experience working with B2B products involving platforms, data, APIs, integrations, infrastructure, or complex enterprise workflows.
- Strong customer-facing experience working directly with senior business leaders, technical stakeholders, and executive sponsors.
- Excellent product judgment with the ability to convert ambiguous problems into clear requirements, prioritized roadmaps, and measurable outcomes.
- Strong program and delivery management skills, including managing multiple workstreams, dependencies, risks, changing scope, and executive-level communication.
- Strong technical fluency and the ability to reason about enterprise software architecture, data and integrations, cloud environments, security, privacy, and software delivery.
- Strong understanding of AI- and LLM-enabled products, including where these technologies create value, their limitations, and the considerations involved in deploying them in enterprise workflows.
- Hands-on prototyping experience with AI-assisted or low-code development tools such as Claude, Cursor, Lovable, Retool, or similar platforms.
- Financial and commercial acumen, including experience evaluating business cases, effort versus value, delivery economics, ROI, and the implications of scope and prioritization decisions.
Preferred qualifications
- Experience deploying AI, machine-learning, LLM, RAG, or agentic solutions into production enterprise environments.
- Familiarity with AI evaluation, guardrails, human-in-the-loop workflows, observability, model performance, and responsible-AI practices.
- Experience working in education technology, workforce transformation, talent intelligence, skills, learning platforms, or other enterprise environments involving complex stakeholder and data ecosystems.
- Experience delivering products or programs across multiple regions, industries, or regulatory environments.
Workplace
- Willingness to collaborate across global time zones and travel periodically for customer discovery, delivery, and executive engagements.
Skills
- APIs
- Claude
- Cursor
- Lovable
- Retool
- LLM
- RAG
- Machine-learning
