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AI Customer Success Manager

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: productboard, Inc
Full Time position
Listed on 2026-06-13
Job specializations:
  • Customer Service/HelpDesk
    HelpDesk/Support
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Productboard Spark: AI built for PMs. Now available & free to try in public beta.

As an AI Customer Success Manager, you’ll help customers adopt AI-first product management by guiding them through Spark - showing them how AI can transform the way they discover, prioritize, build, and communicate. You’ll work directly with product and engineering teams to turn Spark from something they’ve heard about into something they use every day.

You’ll manage your own book of business, lead activation sprints, and build the consultative instincts that make the difference between a customer who uses Spark and one who can’t imagine working without it.

Why this matters for your career

AI is rewriting how product teams work - and this role puts you at the front of that shift, helping real customers move from curiosity about AI to depending on it every day. You won’t just talk about AI-first product management; you’ll coach product and engineering leaders through it hands‑on, using their own data and workflows.

skills you’ll sharpen here - AI fluency and prompt design, consultative solutioning, and translating technical capability into business outcomes - are exactly the skills that will define customer‑facing technical careers for the next decade.

On a Typical Day, You Will...

Guide customers toward AI-first product management — help them see Productboard Spark not as an add‑on but as a core part of how they work. Demonstrate AI‑augmented workflows using the customer’s own data and show how Spark accelerates discovery, prioritization, and roadmap communication.

Manage a book of accounts — build trusted relationships with product leaders, understand their goals, and ensure each account progresses through activation to sustained adoption within allocated service hours.

Deliver activation sprints within the standard playbook — run use case sprints guided by established best practices and templates, escalating when novel or high‑risk situations arise.

Build early AI fluency with customers — configure Spark context so it reflects the customer’s domain, coach users on effective prompting, and follow up with prompt templates and hands‑on support when Spark adoption stalls after the first Sprint.

Support the transition from activation to adoption — structure monthly touchpoints around meaningful signals (MAU Index, Spark usage depth), not vanity metrics, and identify when guidance versus additional hours versus escalation is the right call.

Partner with Account Executives and Renewals Managers — support AE‑led business reviews with product health data, Spark usage metrics, and adoption summaries. Identify expansion signals and surface them to the AE for commercial qualification.

Contribute to internal improvement — share playbook improvements, document solutioning patterns, and support onboarding of new ASEs. Feed observations about customer friction points and process gaps back to the team.

Feed insight into our product direction — share customer patterns and Spark adoption challenges that help Product and Enablement teams improve the platform and our delivery model.

What success looks like

Customers trust you as a credible technical advisor — product leaders seek your guidance on best practices and Spark adoption strategies.

Your accounts consistently hit Time to Value targets.

Monthly touchpoint coverage is at 100% across your book, with success plans current and aligned with customer goals.

Spark usage grows across your accounts as customers move from basic prompts to more integrated workflows, with you coaching the progression.

You deliver use cases within allocated service hours and elevate early when burn rate or scope issues arise.

Renewals in your book are supported with thorough product health data and value documentation, reducing last‑minute scrambles for the AE and RM.

Your playbook feedback and solutioning patterns are picked up by peers, improving how the team delivers.

Customers begin to view Spark as part of how they work, not just a tool they log into — a sign of real adoption taking hold.

About you

Experience in customer success, solutions architecture, implementation consulting, or strategic advisory roles within B2B…

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