Engagement Manager (AI)

Location: Mountain View office with a hybrid schedule

Company

hirify.global is an applied AI research lab creating data, reinforcement learning environments, and specialized agents for frontier labs and enterprises.

What you will do

• Own end-to-end execution of customer engagements across frontier AI labs and enterprise accounts.
• Translate technical requirements between customer ML and research teams and internal engineering, research, and data operations teams.
• Track scope, timelines, SLAs, budgets, and quality across multiple concurrent projects, surfacing risks and proposing solutions.
• Identify account expansion opportunities, scope follow-on projects, and shape proposals with research and product leadership.
• Improve delivery playbooks, tooling, and processes with data operations and engineering.
• Build precise, responsive customer relationships that support long-term partnerships.

Requirements

• 1+ year as an Engagement Manager at a fast-growth data startup.
• 3–6 years of experience in customer engineering, forward-deployed engineering, project leadership, or technical program management.
• Technical foundation in computer science, engineering, mathematics, or another STEM field, with the ability to read technical specifications and communicate with ML researchers.
• Experience managing multiple concurrent workstreams and delivering B2B client-facing projects.
• Strong written communication and an action-oriented, execution-focused approach.
• Familiarity with AI training and evaluation workflows, including reinforcement learning, post-training, agent evaluation, and data labeling at scale.

Nice to have

• Experience working with research or ML engineering teams as a customer or partner.
• Experience in an early-stage or high-growth environment where processes were built from scratch.
• Experience selling into or delivering for technical buyers such as ML platform teams, applied research teams, or AI product organizations.

Culture & Benefits

• Execution-focused environment with technically deep engagements and tight delivery windows.
• Collaboration across research, engineering, data operations, and product teams.
• Opportunity to work on AI training, evaluation, and reinforcement learning environments for frontier labs and enterprises.
• Hybrid work based out of the Mountain View office.