Manager, AI Services Consulting

About the position Customer experience is transforming through AI-driven innovation. At Zendesk, we don’t just embrace this change — we lead it. Our Professional Services team is revolutionizing how we help our customers implement and adopt AI by building an AI Delivery team and methodology. As the Manager, you will be leading a team of consultants who deliver quick time to value while guiding their customers through technical configuration and optimization. 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 consistently delivers fast, measurable customer outcomes on Zendesk AI. You will set clear strategy, standards, and operating rhythm for AI delivery, ensuring the right people are staffed to the right work, projects are tightly scoped and executed predictably, and risks/blockers are escalated and removed quickly. You will align with Sales, Customer Success, and Product on customer roadmaps and success metrics. You will be responsible for continuous improvement in methodology, enablement, and quality so we increase adoption, customer satisfaction, retention, and expansion at scale. Overarching Objective For The Role: Scale a high-performing AI Delivery organization: Hire, onboard, coach, and retain AI Services Consultants; build clear roles, capacity planning, and career development. Deliver predictable, measurable customer outcomes and time to value: Ensure projects are staffed and executed on time and within scope with clear success metrics tied to business impact. Proactively manage risks, technical blockers, and stakeholder alignment to keep implementations moving and value realized through scale. Drive cross-functional alignment and a repeatable AI delivery motion: Partner with Sales, Customer Success, and Product to align on customer AI roadmaps, handoffs, and expansion paths. Use customer insights and delivery data to improve packaging, playbooks, and forecasting—supporting retention and growth. How You’ll Make an Impact Strategic Responsibilities Build and scale the AI Delivery operating model: Define and evolve the delivery methodology, standards, templates, and governance to ensure consistent quality and repeatability across customers and consultants. Own capacity, prioritization, and staffing strategy: Forecast demand, balance utilization vs. customer outcomes, assign the right consultants to the right work, and proactively manage escalations and tradeoffs to protect time-to-value and margin. Drive outcome-based execution and accountability: Ensure your team delivers high quality solutions, delivery meets timelines, scope, and measurable business impact based on the AI Success Roadmap. Lead cross-functional alignment for a unified AI go-to-customer motion: Partner with Sales, Customer Success, and Product on handoffs, customer AI roadmaps, risk management, and expansion plays, creating shared accountability for retention and growth. Develop team capability and product authority at scale: Coach and enable a team of 6–10 consultants through skills development, knowledge management, and technical/product readiness; create feedback loops from the field to improve product, tooling, and enablement.

Responsibilities

• Manage and grow a high-performing team (6–10 direct reports) that consistently delivers fast, measurable customer outcomes on Zendesk AI.
• Set clear strategy, standards, and operating rhythm for AI delivery, ensuring the right people are staffed to the right work, projects are tightly scoped and executed predictably, and risks/blockers are escalated and removed quickly.
• Align with Sales, Customer Success, and Product on customer roadmaps and success metrics.
• Responsible for continuous improvement in methodology, enablement, and quality so we increase adoption, customer satisfaction, retention, and expansion at scale.
• Scale a high-performing AI Delivery organization: Hire, onboard, coach, and retain AI Services Consultants; build clear roles, capacity planning, and career development.
• Deliver predictable, measurable customer outcomes and time to value: Ensure projects are staffed and executed on time and within scope with clear success metrics tied to business impact.
• Proactively manage risks, technical blockers, and stakeholder alignment to keep implementations moving and value realized through scale.
• Drive cross-functional alignment and a repeatable AI delivery motion: Partner with Sales, Customer Success, and Product to align on customer AI roadmaps, handoffs, and expansion paths.
• Use customer insights and delivery data to improve packaging, playbooks, and forecasting—supporting retention and growth.
• Build and scale the AI Delivery operating model: Define and evolve the delivery methodology, standards, templates, and governance to ensure consistent quality and repeatability across customers and consultants.
• Own capacity, prioritization, and staffing strategy: Forecast demand, balance utilization vs. customer outcomes, assign the right consultants to the right work, and proactively manage escalations and tradeoffs to protect time-to-value and margin.
• Drive outcome-based execution and accountability: Ensure your team delivers high quality solutions, delivery meets timelines, scope, and measurable business impact based on the AI Success Roadmap.
• Lead cross-functional alignment for a unified AI go-to-customer motion: Partner with Sales, Customer Success, and Product on handoffs, customer AI roadmaps, risk management, and expansion plays, creating shared accountability for retention and growth.
• Develop team capability and product authority at scale: Coach and enable a team of 6–10 consultants through skills development, knowledge management, and technical/product readiness; create feedback loops from the field to improve product, tooling, and enablement.

Requirements

• People leadership & team scaling: Proven ability to hire, onboard, coach, and retain consultants; set clear expectations, drive performance, and build career paths and progression frameworks.
• Technical and product authority in AI implementations: Strong fluency in AI-enabled customer service workflows, integrations, data readiness, and configuration best practices—able to guide solution design decisions and unblock complex escalations.
• Operational delivery: Define and run team playbooks, KPIs, and SLAs; own tooling or dashboards that provide a single source of truth for delivery and risk.
• Delivery management excellence: Expertise in running multi-workstream delivery with strong scoping, resourcing, risk management, change control, and executive stakeholder communication to ensure predictable outcomes.
• Outcome-based consulting & value realization: Skilled at translating customer goals and roadmaps into technical solutions, defining scope and timelines, and delivering quality implementations.
• Cross-functional influence & GTM alignment: Ability to align Sales, CS, Product, and Services on customer roadmaps, handoffs, and expansion motions; leverage delivery insights to improve packaging, forecasting, and product feedback loops.
• 7+ years in 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.

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