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AnthropicAnthropic

Technical Deployment Lead

Leads enterprise delivery of custom agentic AI solutions from SOW through production, coordinating technical teams, customer stakeholders, scope, architecture trade-offs, and ROI measurement. Requires production AI/ML deployment experience, enterprise delivery leadership, executive presence, and architectural fluency.

About the job

Responsibilities

  • Own technical delivery plans from signed SOWs through production deployment, including milestones, dependencies, success criteria, and value hypotheses.
  • Lead discovery of customer workflows and constraints; pressure-test MVP scope and shape solution architecture with Forward Deployed Engineers.
  • Drive day-to-day execution across internal and customer teams, removing blockers and making scope and priority trade-offs.
  • Author requirements, prioritize engineering backlogs, manage scope, and maintain delivery quality against success criteria.
  • Own customer relationships, including executive briefings and communications with technical, business, procurement, and engineering stakeholders.
  • Define impact hypotheses, baselines, KPIs, and pre- and post-deployment ROI measurement.
  • Develop reusable delivery patterns and communicate field insights to Programs, Product, and Research teams.
  • Navigate security reviews, legal approvals, procurement, compliance requirements, and organizational complexity.
  • Manage changing requirements, contract modifications, risks, escalations, and stakeholder expectations.
  • Run sprint ceremonies, milestone reviews, engagement reporting, and post-sales delivery operations.
  • Travel to customer sites, with up to 25–50% travel expected.

Requirements

  • Experience leading AI/ML engagements or deployments, including AI, ML, or LLM-based agentic solutions in production.
  • Understanding of solution patterns, integration approaches, architecture trade-offs, and real-world deployment challenges.
  • Experience delivering complex, high-stakes technical projects for enterprise clients across multiple workstreams.
  • Ability to navigate architecture discussions and pressure-test technical decisions without necessarily writing production code.
  • Executive presence and credibility with senior business and engineering leaders.
  • Ability to operate independently in ambiguous environments and create structure and repeatable processes.
  • Experience working in a specialized vertical such as life sciences, pharmaceuticals, retail, mining, or agriculture.
  • Bachelor's degree or equivalent combination of education, training, and experience.

Compensation

  • Annual salary: £165,000–£230,000 GBP.

Skills

Artificial Intelligence, Machine Learning, LLMs, AI Agents, Solutions Architecture, Technical Delivery, Product Scoping, Requirements Management, Engineering Backlogs, Kpi Measurement, ROI Analysis, Sow Management, Stakeholder Management, Enterprise Integrations

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