Overview
Own customer deployments of Applied AI products, from initial discovery and product scoping through delivery, adoption, and value realization, working directly with enterprise customers.
What you'll do
- 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.
- Translate customer objectives into a clear product and deployment roadmap covering milestones, workstreams, dependencies, risks, decision points, and launch criteria.
- Create 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.
- Evaluate technical and product trade-offs, challenge assumptions, and ensure proposed solutions are feasible, supportable, secure, and aligned with customer outcomes.
- Partner with engineering teams on AI-specific considerations such as data quality, evaluation approaches, human oversight, model limitations, responsible AI, and production-readiness criteria.
- Define the value hypothesis for each customer engagement and establish the business, adoption, and product metrics required to measure success.
- Evaluate effort, implementation complexity, cost-to-serve, and expected customer value when making scope and prioritization decisions.
- Partner with Sales, Finance, Legal, and Customer Success on scope boundaries, business cases, commercial assumptions, and material changes to customer engagements.
- Translate deployment results into clear narratives on adoption, ROI, customer impact, and future opportunities.
- 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.
What you'll need
- 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.
- Ability to operate effectively in ambiguity, influence cross-functional teams without formal authority, and communicate equally well with executives, product teams, and engineers.
- Willingness to collaborate across global time zones and travel periodically for customer discovery, delivery, and executive engagements.
Nice to have
- 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.
Details
- Location: India.
- Willingness to collaborate across global time zones and travel periodically for customer discovery, delivery, and executive engagements.
Read the full description and apply on the company’s own careers page.