AI Deployment Lead - GTM

Brain Co.•San Francisco, CA

3d•Hybrid

About The Position

Brain Co. is an applied AI startup co-founded by Jared Kushner and Elad Gil, and backed by leading Silicon Valley builders including Patrick Collison and Andrej Gil. We are building AI applications for the world’s most important institutions, delivering impact on real-world problems across governments, healthcare systems, and critical industries. We are looking for leaders who want to help bring new technology into institutions that impact millions of people. We’re hiring a senior AI Deployment Lead to own the end-to-end delivery of our enterprise engagements. You’ll partner closely with clients to understand their goals, drive program success, and turn deployed AI into adopted workflows that stick while owning the commercial agenda within each account and building the trust that grows the relationship over time. You’ll work at the intersection of product, engineering, and the customer. You’ll translate complex needs into partnership proposals, showing both commercial and technical strategy. You’ll then drive a cross functional team to land delivery and the people-and-process change that real adoption demands. From there, drive negotiations and delivery of all expansion efforts. As the voice of the customer, you’ll be accountable for outcomes, not just rollouts. While much of our work anchors in regulated enterprises, a commercially-minded leader could drive deployments across a range of engagements.

Requirements

10+ years of professional experience.
A background in top-tier consulting (McKinsey, Bain, BCG), private equity, investment banking, AI/product companies (e.g., Palantir, Google, Amazon), or technical and operating roles at large enterprises or financial institutions.
Experience working with customers or clients, leading discovery, building trust, and navigating senior stakeholders.
Commercial instinct and/or experience, thinking through value, pricing, and what it takes to win and grow an account, not just the analysis.
Demonstrated success driving both people and process change at large enterprises — operating-model redesign, workflow transformation, and adoption at scale, not just software rollouts.
Comfort with AI and technical concepts, able to work closely with product and engineering and translate between technical and business audiences.
Strong communication and building skills. Ability to turn complex analysis into clear narratives and high-quality materials that move decisions.
Range and ownership. Comfort moving between customer work, analysis, and operations, and thriving in ambiguity: can take things 0 to 1 without waiting for a playbook.

Nice To Haves

MBA or equivalent experience.
Experience supporting or delivering complex, consultative customer engagements.
Experience working with product and engineering teams to scope technical work.
Technical or AI experience — comfort building with, or alongside, AI tools and engineering teams.

Responsibilities

Run discovery and engagement operations, leading structured discovery with customers, developing value sizing and product proposals, mapping their needs, and running the day-to-day rhythm of an engagement so nothing falls through the cracks.
Own end-to-end delivery: own your engagements from kickoff to adoption: lead delivery sprints and deployment timelines, coordinate the cross-functional delivery team, and ensure timely, high-quality, audit-ready solutions in regulated environments.
Define and prioritize features: partner with clients to identify high-impact problems across their workflows, and define the AI-driven product features that address them.
Translate business needs: convert customer requirements and operational pain points into clear technical specifications and use cases for internal engineering teams.
Drive adoption and change management: onboard stakeholders and engage users, lead the people-and-process change required for new ways of working to take hold, and gather direct feedback to drive continuous improvement.
Drive program success and commercial expansion: partner with the client to deliver measurable program outcomes, and own the commercial agenda within each account, building the trust and impact that expand our relationship over time.
Support AI diligence and value creation: contribute to deep-dive assessments of target companies’ AI strategies, data infrastructure, and technical maturity, and help shape plans that connect AI capabilities to commercial outcomes.
Bridge business and technology: translate complex AI/ML capabilities into actionable recommendations for investment committees, portfolio executives, and senior client stakeholders.
Collaborate cross-functionally: serve as the bridge between customers and internal teams, including data scientists, engineers, and product leads.