Enterprise Client Partner (Frontier AI)

About this role

We work with leading AI labs and advanced enterprise teams building frontier models. Our focus is on evaluation systems, reinforcement learning (RL) environments, and high-quality human data pipelines that directly impact model performance. We’re hiring an Enterprise Client Partner to engage deeply with research, engineering, and procurement stakeholders, and to drive high-value partnerships around model evaluation and human data solutions.

Skills

Key responsibilities

• Source and close partnerships with AI labs and ML-driven organizations working on frontier models.
• Lead technical discovery across evaluation workflows, RLHF pipelines, and model improvement loops.
• Engage directly with research leads, ML engineers, and data teams to understand system-level constraints and requirements.
• Translate ambiguous research and engineering needs into well-scoped human data and evaluation programs.
• Structure and negotiate complex, high-value agreements involving data generation, annotation, and evaluation at scale.
• Work cross-functionally with product, research, and operations to ensure delivery aligns with technical expectations.
• Drive expansion through deeper integration into evaluation pipelines and RL environments.
• Provide clear signal on pipeline quality, deal risk, and market dynamics.
• Feed back insights from customers into evaluation frameworks, product direction, and go-to-market strategy.

Required skills & qualifications

• Ability to communicate fluently with ML engineers and research teams (you don’t need to be one, but you can hold your own).
• Experience selling into AI/ML, developer tools, or deeply technical products.
• Strong track record closing complex, multi-stakeholder deals with technical and commercial depth.
• Familiarity with model evaluation, RLHF, or reinforcement learning environments.
• Structured, hypothesis-driven approach to sales and problem solving.
• High agency and comfort operating in ambiguous, fast-moving environments.

Preferred qualifications

• Experience with human data pipelines (labeling, evaluation, synthetic data, RLHF).
• Exposure to frontier model development or benchmarking systems.
• Prior work with AI labs, research orgs, or advanced ML teams.
• Understanding of enterprise procurement in high-value technical deals.