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Senior AI Project Manager

At ASAPP, our mission is simple: deliver the best AI-powered customer experience, faster than anyone else. To achieve that, we're guided by principles that shape how we think, buil

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Asapp 2 New York, New York · Mountain View Source published Sep 9, 2026 Verified 5 hours ago
✓ 100% verification score · Source: Asapp 2 (lever) · Always confirm final requirements on the original source.
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EmploymentFull-time

Overview

At ASAPP, our mission is simple: deliver the best AI-powered customer experience, faster than anyone else. To achieve that, we're guided by principles that shape how we think, buil

Full job description

At ASAPP, our mission is simple: deliver the best AI-powered customer experience, faster than anyone else. To achieve that, we're 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. We're seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it's Day 1. We're 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 you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we'd love to talk. This is more than a job, it's a journey. We are seeking a Senior AI Project Manager to join our Customer Experience organization. In 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

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