Manager, AI Deployment Engineering

Responsibilities

• Build, manage, and develop a high-performing team of Applied AI Engineers serving large enterprise customers.
• Own the quality and impact of work across solution design, implementation, production readiness, adoption, and expansion.
• Coach engineers on architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost decisions.
• Establish account prioritization, coverage, operating, escalation, and repeatable delivery models.
• Serve as a senior technical escalation point for launches, incidents, integrations, and high-stakes customer decisions.
• Partner with customer executives and technical leaders to connect implementation decisions to measurable business outcomes.
• Guide customers from experimentation to production and sustained organizational adoption.
• Collaborate with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal.
• Translate customer needs and implementation challenges into actionable internal product and engineering feedback.
• Develop reusable architectures, evaluation methods, playbooks, tooling, and technical enablement.
• Establish metrics for implementations, adoption, outcomes, delivery quality, team capacity, and reusable work.
• Hire, coach, and develop team members while fostering accountability, collaboration, inclusion, and continuous learning.

Requirements

• Significant experience managing customer-facing technical teams, such as Applied AI Engineers, Solutions Architects, Forward Deployed Engineers, Customer Engineers, or Technical Account Managers.
• Experience leading teams implementing complex software, data, machine learning, or AI systems in enterprise environments.
• Technical depth to evaluate architectures, challenge assumptions, and coach engineers through difficult implementation decisions.
• Experience taking AI, machine learning, or other technically complex systems from prototype to production.
• Understanding of reliability, observability, security, privacy, data governance, evaluation, and operational readiness.
• Experience leading teams through ambiguity, competing priorities, escalations, and evolving products or markets.
• Ability to translate among technical details, customer needs, product strategy, and business outcomes.
• Experience working with large organizations, multiple business units, stakeholder groups, procurement processes, or governance requirements.
• Strong executive presence and ability to build trust with senior technical and business stakeholders.
• Experience designing operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes.
• Strong cross-functional collaboration and resource allocation skills.
• Track record of coaching team members, raising performance, and building inclusive teams.

Relevant Experience

• Applied AI engineering, solutions architecture, forward-deployed engineering, professional services, technical consulting, or customer engineering leadership.
• Generative AI, machine learning, developer platforms, cloud infrastructure, data platforms, or other complex enterprise technology implementations.
• Global customers, multi-business-unit implementations, regulated workflows, or large-scale organizational transformations.
• Technical enablement, reusable solution patterns, evaluation frameworks, or customer implementation methodologies.