AI Deployment Lead

Brain Co.•San Francisco, CA

3d•Hybrid

About The Position

Brain Co. is seeking an AI Deployment Lead to join their team in San Francisco. This role focuses on the intersection of AI product delivery and client engagement, specifically for financial services clients across the U.S. The lead will be responsible for defining, shaping, and driving AI-powered solutions for a range of financial institutions. The position requires owning the end-to-end delivery of engagements, partnering closely with clients to understand their goals, drive program success, and ensure AI solutions are adopted into durable workflows within large, regulated enterprises. The role also involves managing the commercial aspects of client accounts, building trust, and demonstrating impact to grow client relationships. Collaboration with engineers, product managers, designers, investment professionals, and senior stakeholders is key to translating complex financial and commercial needs into actionable technical solutions. The AI Deployment Lead will act as the voice of the customer, lead delivery cycles, contribute to value creation, and build long-term relationships based on trust and measurable impact.

Requirements

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), private equity, investment banking, AI/product companies (e.g., Palantir, Google, Amazon), or technical/operating roles at large enterprises or financial institutions.
Experience contributing to diligence processes, strategic analysis, technical evaluations, or enterprise AI deployments.
Demonstrated success driving both people and process change at large enterprises — operating-model redesign, workflow transformation, and adoption at scale.
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.

Nice To Haves

Direct financial services experience (banking, asset management, insurance, private equity, or fintech).
Startup or high-growth operating experience; comfort with ambiguity and moving fast.
Familiarity with financial data, workflows, and the regulatory considerations relevant to deploying AI in financial services.

Responsibilities

Own the delivery of engagements from kickoff to adoption, leading agile sprints and deployment timelines.
Coordinate the cross-functional delivery team to ensure timely, high-quality, audit-ready solutions in regulated environments.
Partner with clients to identify high-impact problems and define AI-driven product features.
Convert customer requirements and operational pain points into clear technical specifications and use cases for internal engineering teams.
Engage users and onboard stakeholders, leading the people-and-process change required for new ways of working.
Gather direct feedback to drive continuous improvement.
Deliver measurable program outcomes and own the commercial agenda within each account.
Support deep-dive assessments of target companies' AI strategies, data infrastructure, and technical maturity.
Shape plans that connect AI capabilities to commercial outcomes.
Translate complex AI/ML capabilities into actionable recommendations for investment committees, portfolio executives, and senior client stakeholders.
Serve as the bridge between customers and internal teams including data scientists, engineers, and product leads.