About Us At Pareto.AI, we’re on a mission to enable top talent around the world to participate in the development of cutting-edge AI models.

In coming years, AI models will transform how we work and create thousands of new AI training jobs for skilled talent around the world. We’ve joined forces with top AI and crowd researchers at Anthropic, Character.AI, Imbue, Stanford, and University of Pennsylvania to build a fair and ethical platform for AI developers to collaborate with domain experts to train bespoke AI models.

About The Role Pareto is hiring its first Head of AI Engagement Management , responsible for building and leading the function that owns customer relationships, engagement health, and long-term success across our most strategic AI accounts. This role blends player-coach execution with organizational design. You will directly manage a small portfolio of Tier-1 customers while building a high-performance Engagement Management (EM) team. EM owns relationship depth, technical credibility, retention, and expansion in close partnership with Delivery and Sales. You own the long-term success, retention, and growth of Pareto’s most critical AI customers. You will act as a trusted advisor to researchers, PMs, and engineering leaders shaping next-generation AI systems and ensure Pareto remains a valued execution and thought partner.

Key Responsibilities Build and Lead the Engagement Management Function

• Define the operating model, charter, and workflows for EM.
• Establish segmentation (Tier 1 vs Tier 2 accounts, verticals, pods) and scalable playbooks for engagement planning, QBRs, renewals, and expansion.
• Set and track core metrics: retention, expansion, account health, NPS/CSAT, and referenceability.
• Serve as the connective tissue between Sales, Delivery, and Product to ensure a unified customer experience.

Hire, Develop, and Lead the EM Team

• Recruit, onboard, and coach EMs.
• Define expectations, leveling standards, and performance rhythms.
• Build a culture of high ownership, technical curiosity, and disciplined execution.

Direct Ownership of Strategic Accounts (Player-Coach)

• Serve as primary point of contact for 1–2 flagship AI lab/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.

Solution Design, Scoping & Commercial Strategy

• Partner with Product, Delivery, and Engineering to design solutions for 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.
• Implement renewal processes across timing, stakeholder alignment, and messaging.
• Build early-warning systems for churn and coordinate cross-functional mitigation plans.

Cross-Functional Leadership

• Partner with Sales on new-logo vs. expansion ownership and seamless handoffs.
• Work closely with Delivery to ensure EMs and DDLs show up as a unified team.
• Collaborate with Product/R&D to bring structured customer insights into roadmap planning and ensure EM fluency on upcoming capabilities.

What Success Looks Like Organizational Impact

• High retention and expansion across key accounts with minimal surprise churn.
• Smooth cross-functional execution with Sales and Delivery.
• EM team that confidently engages researchers and technical buyers.
• Repeatable playbooks enabling consistent performance and fast onboarding.
• Zero renewal risk due to engagement or relationship issues.

Qualifications

• 8+ years in customer-facing roles with technical buyers (Engagement Management, Strategic Accounts, CS, GM, or product-minded ML/data roles).
• 3+ years leading teams, including hiring, coaching, and performance management.
• Experience managing complex, multi-stakeholder accounts (AI labs, model builders, or R&D-heavy orgs preferred).

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.

Compensation Range: $200K - $270K