Engagement Management Lead

Handshake•San Francisco, CA

31d

About The Position

Help leading AI labs and enterprises turn Handshake AI into measurable value-by designing, launching, and scaling programs that shape how frontier models are trained and deployed. As an Engagement Management Lead, Handshake AI, you'll own our most important customer relationships end-to-end, from scoping and onboarding through production deployment, expansion, and renewal. You'll sit at the intersection of customers, operations, product, and engineering-turning ambiguous goals into clear programs, and orchestrating cross-functional teams to deliver results.

Requirements

6+ years in customer-facing, high-ownership roles (engagement management, consulting, customer success, strategy & operations, or similar) ideally with AI, data, or complex operational products.
Proven track record leading complex, multi-stakeholder implementations and driving measurable business outcomes for enterprise customers.
Experience working with senior stakeholders (VP/C-level) and navigating complex organizations.
Strong program and project management skills across multiple concurrent workstreams.
Comfort with data and metrics-defining KPIs, doing simple analyses, and telling a clear story with numbers.
Understanding of AI / ML or data-driven products and how LLMs are trained, evaluated, and used in real workflows.
Ability to translate business goals into concrete scopes, timelines, and success criteria.

Nice To Haves

Management consulting experience strongly preferred.

Responsibilities

Leading strategic implementations for key Handshake AI accounts, from scope and milestones through on-time, successful go-live.
Owning the full engagement lifecycle (onboarding, delivery, QBRs, expansions, renewals) as the single-threaded owner of value for a portfolio of strategic customers.
Translating customer needs into clear programs and requirements, influencing product, operations, and roadmap decisions.
Defining and reporting on success metrics (business KPIs, SLAs, model quality) and using data to guide decisions and expansions.
Partnering with Sales on seamless pre- to post-sales handoffs and identifying upsell / cross-sell opportunities.