AI Engagement Manager
Manages strategic AI lab accounts as trusted advisor, owning relationships, solution design for ML workflows like RLHF and data labeling, renewals, expansions, and health metrics for long-term success.
About the job
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
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
Skills
Machine Learning, RLHF, Data Labeling, Evaluation, Red-Teaming, Agentic AI, Ml Workflows, Customer Success, Account Management
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