Technical Engagement Manager – AI/ML (HealthCare)

The Engagement Manager will lead a forward deployment engineering POD embedded within a medical device client environment. This role is both technical and commercial, operating at the intersection of video-based machine learning, data-driven use case discovery, and customer-facing program execution. The Engagement Manager will work directly with the client’s sales organization and their end customers, often on-premises, to identify, shape, and deliver high-impact video data monetization opportunities.

Responsibilities

Act as the primary point of contact between the client’s sales channel, end customers, and the deployed engineering POD; Lead discovery sessions, on-site observations, and requirements gathering for video-based machine learning opportunities; Translate observed workflows and customer challenges into structured AI/ML use cases; Work with data scientists and ML engineers to scope model development, data preparation, and validation activities; Drive the full lifecycle of engagement execution—from opportunity identification through delivery and customer success; Ensure technical alignment, risk management, and timeline adherence across cross-functional teams; Shape and present commercial proposals, ROI analyses, solution roadmaps, and value narratives; Manage stakeholder communication, reporting, and executive updates; Ensure compliance with healthcare/medical device regulatory standards when working with sensitive video data; Promote a culture of experimentation, rapid iteration, and hypothesis-driven development within the POD

Requirements

8+ years of experience in customer-facing delivery, technical program management, or AI/ML engagement leadership; Strong understanding of machine learning concepts, especially video analytics, computer vision, and supervised learning workflows; Experience working in healthcare, medical devices, or regulated environments involving sensitive data; Ability to translate ambiguous customer needs into well-scoped technical requirements; Excellent communication, storytelling, and client management skills; Proven ability to work on-premises with customers, driving hands-on discovery and solution design; Strong commercial acumen with experience in pricing, proposal creation, and value-modeling; Ability to lead cross-functional engineering teams in a dynamic, field-deployed setting

Nice to have

Background in data science, computer vision, or ML engineering; Prior experience in forward deployment engineering, field engineering, or consulting; Knowledge of FDA/medical device regulatory frameworks; Familiarity with video annotation tools, model training pipelines, and edge-deployment workflows