Technical Project Manager - Enterprise AI Solutions

Role Overview

Technical Project Manager (Enterprise AI Solutions) at Snorkel AI. Lead the day-to-day delivery of high-impact AI projects with enterprise customers and internal technical teams, turning AI use cases into successful, production-ready solutions.

Responsibilities

• Lead day-to-day delivery across enterprise AI engagements, ensuring alignment to scope, schedule, budget, milestones, and customer outcomes.
• Create and maintain detailed project plans (workstreams, deliverables, dependencies, ownership, timelines, and resourcing needs).
• Maintain Jira and project documentation as sources of truth for decisions, risks, status, and commitments.
• Run project cadences: convert discussions into clear actions and decisions, and drive commitments to completion across Snorkel and customer teams.
• Identify and manage risks, blockers, dependencies, and scope changes early; develop mitigations and escalate when needed.
• Provide clear project reporting and act as the trusted day-to-day customer contact for delivery progress, risks, decisions, and next steps.
• Develop enough technical fluency to connect work on agents, RAG, evaluation, knowledge bases, classification, and extraction to customer goals.
• Partner with Operations on project financials, coordinate closeout, and help improve delivery standards, tools, and playbooks.

Requirements

• 2+ years in project management, delivery, project coordination, or technical program management (preferably professional services, consulting, or enterprise software).
• Proven ability to manage multiple workstreams and deliver on schedule and within budget.
• Strong organization, communication, and stakeholder management, including experience with senior enterprise customers.
• Technical aptitude to build working knowledge of AI concepts: agents, RAG, evaluation, knowledge bases, classification, extraction.
• Proficiency with Jira and strong discipline around documentation accuracy.
• Comfortable working in ambiguity and adapting as priorities evolve.
• Travel up to 15%.

Nice to Haves

• Not explicitly stated, but success likely depends on growing technical fluency and experience in AI/ML delivery contexts.