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AI Deployment Lead

Brain Co.· GTM
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Hybrid (San Francisco Bay Area), Hybrid (Remote)Full-timePosted 3mo ago

About the role

Senior AI Deployment Lead responsible for end-to-end delivery of enterprise AI engagements, driving adoption, commercial expansion, and cross-functional coordination across product, engineering, and customers in regulated environments.

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.

Qualifications

  • 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.

Skills

Required:Discovery and engagement managementEnd-to-end delivery leadershipProduct feature prioritization for AIRequirements translation (business to technical)Change management and adoptionCommercial and account expansionExecutive communicationCross-functional collaboration
Nice to have:AI strategy diligence

Benefits

  • Competitive compensation including salary, equity, and performance incentives.
Last updated Sep 24, 2026. Interested? Apply on the company site.

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