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Anthropic is hiring a Manager of Technical Deployment for Financial Services to lead a team of Technical Deployment Leads (TDLs) embedded with strategic financial services customers. This is a player-coach role that combines hands-on delivery leadership with team management and portfolio oversight.
You will hire, develop, and retain a team of TDLs who embed with Fortune 100 financial institutions to ship production AI applications using Claude. You own engagement portfolio health across the financial services vertical, setting delivery quality standards and building playbooks that enable the practice to scale. Your responsibilities include managing direct reports through regular 1:1s and clear feedback, owning customer outcomes and executive relationships, making staffing decisions for each engagement, and leading the most complex engagements yourself when regulatory exposure or organizational complexity demands it.
Key responsibilities include: hiring and developing TDLs; tracking engagement health and intervening when delivery drifts; holding executive relationships with customer sponsors; setting the bar for delivery excellence (SOW quality, MVP scoping, value measurement); codifying reusable solution patterns and technical playbooks; partnering with Sales on engagement qualification and scope; running team operating rhythm and engagement reviews; and surfacing field lessons back to Product and Research teams.
You will travel to customer sites 25–50% of the time. This role requires deep credibility in architecture conversations with engineering leads and comfort in executive-level sales conversations. You won't write production code but will pressure-test technical decisions made by your team and embedded Forward Deployed Engineers.
The ideal candidate brings 8+ years leading enterprise AI/ML delivery (as founder, engineer, data scientist, or researcher transitioning to deployments) with at least 3 years directly managing people who owned delivery outcomes. You have built and led technical delivery teams in enterprise environments, ideally including embedded or forward-deployed teams at client sites. You have shipped AI, ML, or LLM-based agentic solutions to production and understand solution patterns, integration approaches, and real-world failure modes. You bring depth in Financial Services—having delivered technology programs inside banks, insurers, or asset managers, understanding model risk, security, and compliance review processes, and able to speak credibly with CIOs, chief risk officers, and heads of engineering. You can navigate architecture discussions, evaluate technical trade-offs, and judge whether proposed agent designs are realistic.
