Jobs Companies Pareto.AI AI Engagement Manager

À propos de ce poste AI Engagement Manager chez Pareto.AI

Pareto.AI · US Remote

About Pareto

Humanity is in a virtuous cycle: human insight improves AI, and better AI expands what people can do. Sustaining it depends on the one input that can't be automated: expert human judgment.

At Pareto, we build the platform that turns that judgment into the data, evals, and RL environments frontier models learn from. We work with leading frontier labs like Anthropic and GDM, and we give skilled people everywhere a way to shape the future of AI and share in what it creates.

This RL environment and human-data infrastructure is already in production. Our job now is to scale it.

About the Role

Pareto is hiring an AI Engagement Manager responsible for owning customer relationships, engagement health, and long-term success across our most strategic AI accounts. This role blends technical credibility with relationship depth — you will manage a portfolio of Tier-1 customers, serving as a trusted advisor to researchers, PMs, and engineering leaders shaping next-generation AI systems. You ensure Pareto remains a valued execution and thought partner across the full customer lifecycle.

Key Responsibilities

Own Strategic Customer Relationships

  • Serve as the primary point of contact for a portfolio of flagship AI lab and model-builder accounts

  • Build multi-threaded relationships across researchers, PMs/TPMs, vendor ops, and procurement

  • Map complex org structures, identify champions, and uncover expansion opportunities

  • Act as a trusted advisor who deeply understands each customer's technical goals and roadmap

Solution Design, Scoping & Commercial Strategy

  • Partner with Product, Delivery, and Engineering to design solutions for Agentic AI, data labeling, evaluation, RLHF, red-teaming, and emerging workflows

  • Ensure strong requirements gathering, alignment on success metrics, and clear translation into operational workflows

  • Maintain standards for scoping, SLAs, quotes, and margins

  • Translate research-driven technical requirements into clear, implementable workflows with Delivery and Product

Account Health, Renewals & Expansion

  • Maintain living account plans outlining use cases, risks, and growth opportunities

  • Drive renewal processes across timing, stakeholder alignment, and messaging

  • Build early-warning systems for churn and coordinate cross-functional mitigation plans

  • Track core account metrics: retention, expansion, account health, and NPS/CSAT

Cross-Functional Collaboration

  • Partner with Sales on new-logo vs. expansion ownership and seamless handoffs

  • Work closely with Delivery to show up as a unified team to customers

  • Collaborate with Product/R&D to bring structured customer insights into roadmap planning

What Success Looks Like

  • High retention and expansion across your account portfolio with minimal surprise churn

  • Customers who view you as a genuine thought partner, not just a vendor contact

  • Smooth cross-functional execution with Sales and Delivery

  • Repeatable, proactive engagement that surfaces risks and opportunities early

Qualifications

  • 4+ years in customer-facing roles with technical buyers (Engagement Management, Strategic Accounts, Customer Success, or product-minded ML/data roles)

  • Experience managing complex, multi-stakeholder accounts (AI labs, model builders, or R&D-heavy orgs preferred)

  • Working knowledge of ML/data workflows (data labeling, evaluation, RLHF, red-teaming, or adjacent)

  • Demonstrated ability to lead solution design and scoping with Delivery/Ops

  • Experience owning or co-owning renewals, expansions, and commercial outcomes

  • Ability to navigate procurement and vendor ops in enterprise settings

  • Excellent communication across researchers, PMs, executives, and procurement

  • High ownership, decisiveness, and comfort in rapidly changing environments

Nice to Have

  • STEM background or strong technical fluency (CS, Engineering, Stats, ML, Economics)

  • Experience at an AI data provider, ML infra platform, or developer tools company

  • Existing relationships within the AI/ML ecosystem

  • Experience working in R&D-driven organizations

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