ZendeskManager, AI Success Strategist, Customer Success
Job Description
Why This Role? Why Now?
Customer experience is transforming through AI-driven innovation. At Zendesk, we don’t just embrace this change — we lead it. As the Manager, AI Success Strategists will scale our AI-driven Resolution Platform by building and leading a team of strategists who deliver predictable, measurable AI outcomes for customers. This role blends deep product expertise with people leadership: you’ll be both the product authority for your team and the coach who develops their skills to deliver at scale.
Mission
You will manage and grow a high-performing team (6–10 direct reports) that owns end‑to‑end delivery of customers’ AI roadmaps. You’ll translate product capabilities into clear business strategies, ensure consistent execution across customers, and maintain recurring outcome-driven cadences that secure retention and expansion. Success is measured by customer satisfaction, adoption of automated resolutions, retention improvements, and a team that reliably forecasts and mitigates risk.
Overarching Objective For The Role:
Own and scale a 6–10 person AI Success Strategist team to deliver predictable, measurable customer AI outcomes — e.g., drive double‑digit increases in automated resolution adoption, shorten time‑to‑value for deployments, and materially improve account retention and expansion metrics (GRR/NRR)
Operationalize repeatable playbooks, SLAs, and account‑level forecasting so the team detects and mitigates risk earlier, improves forecast accuracy, and reduces at‑risk accounts — turning reactive firefights into steady, measurable adoption curves
Hire, coach and develop individual contributors to raise team delivery velocity and quality: establish clear career paths, lift performance metrics, and ensure consistent, outcome‑focused executive engagement that converts strategic customers into referenceable success stories
Own account‑level delivery, adoption and forecast accuracy for a defined portfolio; responsible for X% lift in automation adoption, Y% reduction in time‑to‑value, and Z decrease in at‑risk accounts year over year
How You’ll Make an Impact
Strategic Responsibilities
Org leadership & people strategy: Own hiring, onboarding, and day‑to‑day development for your AI Success team (6–10). Coach ICs, run performance cycles, create clear career paths, and track team health and retention metrics.
Strategic product partnership & roadmap influence: Be the product expert for your team—translate portfolio signals from your accounts into clear product feedback and prioritized tasks. Work closely with Product on pilot execution and beta validation to de‑risk customer deployments.
Operational ownership & cross‑functional coordination: Run repeatable playbooks, KPIs, and delivery SLAs for your team. Coordinate handoffs with Sales, Professional Services, Product, Partners, and RevOps to remove blockers and enable rapid context‑switching across accounts.
Executive engagement & external relationships: Own executive relationships at the account level and personally lead C‑level briefings for strategic customers. Coach your team to prepare and run scalable, outcome‑focused executive interactions.
Portfolio‑level risk forecasting & business insight: Maintain predictive health scores and account‑level forecasts for your portfolio. Identify trends and early risks, surface prescriptive mitigations to stakeholders, and improve forecast accuracy and time‑to‑detection for at‑risk accounts.
Commercial outcomes & growth: Drive adoption and expansion plays within your portfolio—own account targets for adoption, retention, and expansion velocity. Collaborate with Sales and Finance on renewal strategy and tactical expansion motions.
Responsible AI governance & policy guidance: Advise customers on practical, engagement‑level AI guardrails (explainability, data handling, compliance). Escalate complex governance issues to Product/Legal/Security and ensure your team is trained on responsible‑AI best practices.
What You’ll Need to Succeed
Strategic Skills & Expertise
Product partnership track record: Proven ability to translate account signals into validated product asks and run pilots/betas; escalate strategic asks to Director. Translate account signals into validated product asks and run pilots/betas; escalate strategic asks to Director
Product & technical fluency: Deep familiarity with generative AI, integrations, and authentication—able to map features to customer journeys and unblock adoption with ProdDev/Engineering.
Forecasting & risk management outcomes: Built and operated account‑level predictive health scores and adoption forecasts that improved forecast accuracy and enabled early mitigations.
Operational delivery: Defined and ran team playbooks, KPIs, and SLAs; owned tooling or dashboards that provide a single source of truth for adoption and risk.
Executive presence: Comfortable briefing customer executives (up to VP/CxO) and presenting account‑level trends and forecasts to internal stakeholders with clear, concise materials.
Commercial impact: Track record owning team targets for adoption, retention, and expansion—with measurable improvements in GRR/NRR, automation adoption, or expansion outcomes.
People leadership: Proven experience managing, coaching, and developing individual contributors (6–10), including hiring, performance cycles, and career development.
Change & strategic judgment: Demonstrated ability to convert account insights into prioritized product tasks or tactical GTM adjustments and to drive follow‑through.
Mindset: Entrepreneurial ownership, bias for action, and comfort operating with ambiguity while enforcing disciplined measurement and accountability.
Qualifications
7+ years in Customer Success / Professional Services / Technical Account Management / Solutions Consulting in enterprise SaaS; 2+ years in AI-related roles or working on AI product adoption.
2+ years of people management experience leading customer-facing teams (6–10 direct reports).
Previous experience in go-to-customer/GTM roles in enterprise technology / SaaS — either customer success management, professional services/consulting, technical account management, or solutions engineering/pre-sales consulting
Demonstrated experience in using adoption and health analytics to forecast churn and expansion; surface early risk signals and recommended mitigations to secure retention and growth.
Bachelor’s degree in Business, Computer Science, Engineering, or related field; advanced degrees; certifications in AI strategy or project management preferred.
Demonstrated product expertise: ability to translate generative AI features, integrations, and technical requirements into business outcomes.
Proven cross-functional influence with Product and Engineering; experience surfacing product feedback and driving prioritization.
Track record of building predictive adoption models, using analytics to forecast churn/expansion and operationalizing mitigations.
Excellent communication skills; ability to distill complex AI concepts for executives and technical teams.
AIAA
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Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.
The intelligent heart of customer experience
Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
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