Senior AI Project Manager
Mountain View, CA - USA
Job Summary
At ASAPP our mission is simple: deliver the best AI-powered customer experience faster than anyone else. To achieve that were guided by principles that shape how we think build and execute. We value customer obsession purposeful speed ownership and a relentless focus on outcomes. We work in tight skilled teams prioritize clarity over complexity and continuously evolve through curiosity data and craftsmanship.
Were seeking technologists and problem solvers who thrive in fast-paced environments love collaborating with great talent and approach every day like its Day 1. Were a globally diverse team with hubs in New York City Mountain View Latin America and India. This role is hybrid based out of either our New York City or Mountain View office and candidates should be comfortable coming in two to three days a week. If youre driven by continuous learning rapid pivots and the challenges of building in a high-growth startup wed love to talk. This is more than a job its a journey.
We are seeking a Senior AI Project Manager to join our Customer Experience this role you will manage customer-facing software and AI delivery projects from initiation through closure coordinating across technical and business teams to ensure clear communication predictable execution and a high-quality customer experience. You will play a central role in driving delivery discipline across our most strategic enterprise engagements. This is a player-coach role meaning you are equally comfortable rolling up your sleeves on the work itself as you are mentoring and elevating the people around you.
Manage software and AI delivery projects end to end ensuring alignment with scope timelines and customer expectations across the full project lifecycle.
Build and maintain project plans schedules and core delivery documentation to support transparency and accountability across teams.
Communicate project status risks and dependencies clearly to enterprise customers and internal stakeholders including executive leadership.
Coordinate cross-functional teams spanning Solutions Engineering Product and Customer Success through each phase of delivery.
Support escalation handling with professionalism and timely follow-through serving as a steady point of contact for customers navigating complex deployments.
Contribute to PMO best-practice development and continuous improvement efforts as our delivery organization scales.
Adjust project plans proactively in response to changing priorities customer needs or evolving product capabilities.
5 years managing customer-facing software or SaaS delivery projects with a track record of successful enterprise-scale engagements
Experience delivering projects across Agile Waterfall or hybrid methodologies in technical or AI-adjacent environments
Strong problem-solving and risk-management abilities with a bias toward proactive communication over reactive escalation
Effective stakeholder engagement skills with demonstrated ability to operate across both technical and executive audiences
A player-coach mindset with the ability to lead by example stay close to the work and develop the people around you
PMP certification preferred
Experience managing conversational AI LLM or NLU delivery projects in a customer-facing context
Ability to assess AI use cases at a foundational level and support evaluation of data readiness and model performance considerations
Familiarity with prompt engineering concepts AI governance basics and guardrails as they relate to enterprise deployments
Experience helping customers set realistic expectations across AI and generative AI implementations
Comfort identifying and tracking AI-specific risks including data quality issues model behavior and hallucination-related considerations
Active use of AI tools in daily work for automation analysis or documentation
Required Experience:
Senior IC
About Company
Improve customer experience and radically increase CX performance at the same time. This AI-NativeĀ® software platform provides AI-driven predictions on what agents should and do throughout each interaction and increasingly automates routine tasks before, during, and after the conversa ... View more