AI Deployment Lead

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 Karpathy. 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. Our progress so far:

• Automated construction permitting for a sovereign government → 80% faster, unlocking $375M+ in value

• Optimized supply chains for a leading global energy company → 30% lower cost, 99% reliability, preventing $100M+ in losses

• Streamlined hospital patient care across national health systems → 40% better outcomes, 80% less admin work

Company momentum:

• Raised a $55M Series A from leading investors

• Built a team of 70+ AI experts from Tesla, Google DeepMind, NVIDIA, and Databricks

We're building out our AI Deployment team in San Francisco, with a focus on financial services clients across the U.S. In this role, you'll work at the intersection of AI product management and client engagement — helping define, shape, and drive AI-powered solutions for banks, asset managers, insurers, private investors, and their portfolio companies. While financial services is our anchor, a strong, commercially-minded leader could also drive deployments across other enterprise engagements.

You'll own the end-to-end delivery of your engagements — partnering closely with the client to understand their goals, drive program success, and turn deployed AI into adopted, durable workflows inside large, regulated enterprises. You'll also own the commercial agenda within each account, building trust and demonstrating the impact that grows our relationship with the client over time.

You'll collaborate closely with engineers, product, design, and senior stakeholders to translate complex needs into actionable technical solutions. As the voice of the customer, you'll lead product development and delivery cycles and build long-term relationships grounded in trust and measurable impact.

• Own End-to-End Delivery — Own the delivery of your engagements from kickoff to adoption: timely, high-quality, production-grade products fully adopted in regulated environments.

• Define & Prioritize Features — Partner with clients to identify high-impact problems across their workflows and define AI products to address them.

• Translate Business Needs into Product Spec — Convert user requirements and operational pain points into clear technical specifications for internal engineering and design teams.

• Drive Adoption & Change Management — Engage users and onboard stakeholders; 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 & 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.

• Collaborate Cross-Functionally — Serve as the bridge between customers and internal team of engineers and designers.

• 5+ years of professional experience with meaningful exposure to AI and how it gets deployed in complex, real-world environments.

• Background in top-tier consulting (McKinsey, Bain, BCG), AI/product companies (e.g., Palantir, Google, Amazon), or technical/operating roles at large enterprises or financial institutions.

• Direct financial services experience (banking, asset management, insurance, private equity, or fintech) is a significant plus — but we're just as interested in an exceptional, commercially-minded generalist who can ramp fast in a new domain and lead deployments across a range of engagements.

• Experience contributing to diligence processes, strategic analysis, technical evaluations, or enterprise AI deployments.

• Startup or high-growth operating experience a plus; comfort with ambiguity and moving fast.

• Demonstrated success driving both people and process change at large enterprises — operating-model redesign, workflow transformation, and adoption at scale, not just software rollouts.

• Ability to win over skeptical stakeholders, align competing incentives, and lead organizations through the behavioral change new technology demands.

• Strong technical literacy in AI/ML, with the ability to evaluate data pipelines, model strategies, and infrastructure at a high level.

• Ability to discuss and assess technical trade-offs with engineering teams and translate them for non-technical investment and business audiences.

• Familiarity with financial data, workflows, and the regulatory considerations relevant to deploying AI in financial services is a strong plus.

San Francisco preferred. Regular travel to customers and Brain Co. offices will be expected.