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Open nowPosted 33 days ago

AI Customer Success Engineer

Productboard21 open roles

Pay
$106,000 a year
Where
San Francisco
Work mode
Hybrid
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Your applicationOpen nowAI Customer Success EngineerProductboard · San Francisco

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Share of postings closed within
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  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 33 days ago

The posting

The opportunity

As an AI Customer Success Engineer, 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.

The 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.

Our Tech Stack Productboard, Slack, Salesforce, Google Suite, Zendesk, Claude, Zoom, Gong, Jira, GitHub, Loom.

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 escalate 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 SaaS. Direct experience managing a portfolio of accounts across the post-sales lifecycle — activation, adoption, and renewal support. Comfortable leading conversations with Director and VP-level product leaders — skilled in objection handling and solutioning across varied customer contexts and types. Solid product management knowledge — familiar with discovery methods, prioritization frameworks (RICE, Value vs. Effort), OKRs, and roadmap communication. You understand the workflows Spark is designed to improve. 1–2 years of hands-on AI experience in a professional context — not just personal productivity, but actively using AI to deliver customer outcomes, accelerate workflows, or build AI-augmented solutions. You understand prompt engineering fundamentals, can design basic multi-step AI workflows, and have coached others on effective AI usage. Familiar with enterprise product management tools and integration ecosystems — Jira, Slack, Salesforce, and similar platforms. Strong customer-facing communication and relationship-building skills — you adapt your approach based on the audience and build trust through reliability, follow-through, and genuine curiosity about the customer’s business. Self-motivated and organized — you manage your book of business independently day-to-day, ask for help on the right things, and contribute positively to team culture.

Bonus: Hands-on experience with Productboard or Spark. Background as a product manager yourself, not only advising them. Experience in a high-growth or startup B2B SaaS environment.

The expected base pay range for this position in the San Francisco area is $106,000-$142,00 In addition to the base pay, this role is eligible for competitive at 15% additional variable component, equity awards, and benefits.

Productboard's pay ranges are determined by role, level, and location. Within the range, the successful candidate's starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future.

You can look forward to the following benefits + More

💰Competitive compensation, stock options, company 401k 📚 Budget for online courses, books, and conferences 🏝️ Flexible PTO and paid sick days 🚆 Commuter Benefits 🫶 Volunteer Day for you to help causes close to your heart 🥕 Carrot Fertility Benefits 🥗 Free snacks, drinks, and yummy catered lunches 🏋️‍♂️ Company contribution to gym and wellness memberships ⏰ Flexible working hours and home office. Hybrid Schedule Mon/Tues/Thurs In Office 🍀 Mental Wellness Program to support your well-being and self-care

By applying you agree to Productboard's Global Candidate Privacy Policy

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