AI Deployment Lead - GTM

Brain Co. is an applied AI startup focused on delivering impactful AI applications for critical industries. The AI Deployment Lead will be responsible for the end-to-end delivery of enterprise engagements, ensuring successful adoption of AI solutions and managing client relationships.

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