AI Deployment Lead

Rippling•San Francisco, CA

About The Position

Rippling is launching Rippling AI Solutions, a business line offering custom applications and AI point solutions as well as turnkey AI consulting and implementation services, with a focus on G&A and other non-R&D organizations. The team helps customers identify, design, build, and ship production AI workflows and supports adoption and change management to connect automation to measurable ROI. Solutions may include Rippling, third-party AI tools, and custom workflows; the team is model agnostic. This is a founding role on the AI Solutions team. The AI Deployment Lead owns customer engagements end to end, from discovery through measurable impact. The role combines AI transformation leadership—identifying opportunities, creating transformation roadmaps, managing client relationships, and driving adoption—with forward-deployed product management, translating customer workflows into requirements and shipping solutions with Forward Deployed Engineers (FDEs). The position reports to the General Manager of AI Solutions and works closely with FDE, Product, and Sales. The role will help build a repeatable AI Solutions motion and scale it across customers.

Requirements

5 to 10 years of experience as a commercially minded product manager, technically minded consultant, deployment lead, solutions lead, implementation lead, or similar operator in a high-growth environment.
Experience leading complex, cross-functional programs from ambiguous problem framing through production launch, adoption, and measurable impact.
Ability to communicate clearly with C-level sponsors, operators, end users, product leaders, and engineers.
AI fluency, including sufficient depth in LLMs, agents, retrieval, evaluations, data, APIs, and integrations to scope solutions, write precise requirements, and earn technical teams’ trust.
Ability to map workflows, understand time and cost drivers, quantify the value of changes, and build credible business cases.
Comfort working in zero-to-one environments where playbooks may not exist and need to be defined.
Highly customer-facing, structured, and pragmatic approach, with judgment to balance ambition, feasibility, and speed.
Hands-on use of AI through side projects, prototypes, automations, or practical experimentation, with the ability to explain what worked, what failed, and why.

Nice To Haves

Experience at a forward-deployed, applied AI, or technical services organization.
Experience in HCM, payroll, ERP, finance systems, or G&A workflows.
Experience serving executive buyers and mid-market customers.
Ability to prototype or write light code, especially in Python or SQL.
Experience hiring, coaching, or building a delivery team.
Founder, early-stage operator, or other entrepreneurial experience.

Responsibilities

Serve as the customer’s day-to-day lead from kickoff through value realization, working with executive sponsors, operators, and end users.
Align the General Manager, Sales, FDEs, and the customer on scope, success criteria, and the path to launch.
Run engagement operating cadences, including status updates, steering committees, risks, decisions, and executive readouts.
Diagnose customer workflows and identify high-value opportunities for AI-driven operating leverage.
Create sequenced, quantified, and prioritized AI transformation roadmaps with baselines, target KPIs, and success measures.
Determine where Rippling, third-party AI tools, and custom workflows can create value.
Translate customer workflows into MVP definitions, requirements, acceptance criteria, and evaluation criteria in partnership with FDEs.
Manage implementations with FDEs from scoping through testing, launch, and iteration.
Pressure-test solution designs with FDEs across architecture, integrations, data access, permissions, and edge cases.
Lead training, workflow redesign, and change management to encourage adoption and trust in shipped workflows.
Measure realized value against baselines and turn results into case studies, references, and expansion opportunities.
Codify repeatable patterns into playbooks, templates, ROI models, and product feedback.
Refine the AI Solutions playbook across discovery, scoping, delivery, adoption, ROI measurement, and expansion.
Help turn early engagements into a repeatable motion that can scale across customers and future AI Deployment Leads.
Partner with the GM and FDE leadership on engagement health, staffing needs, delivery capacity, and the evolution of the motion as it scales.