Client Director, Frontier Data - US

Operational Leadership & Performance Management

Lead and scale global delivery teams of 100+, distributed across functions, regions, and levels (ICs, leads, and managers)

Implement performance management systems that go beyond managerial reporting using data-driven metrics, tools, and products to assess productivity, quality, and output consistency

Build strong operational structures that allow for transparency, accountability, and early detection of underperformance

Partner with cross-functional leads to optimize workflows and improve internal tool adoption for delivery efficiency

Data Quality & Scripting-Driven Automation

Own the quality, accuracy, and scalability of data generated for LLM training

Move beyond manual QA layers by leveraging Python scripting, APIs, and automation frameworks to measure, validate, and improve dataset integrity

Design and oversee tools or scripts for data validation, annotation accuracy checks, and pipeline consistency

Ensure datasets adhere to compliance standards (PII, GDPR, HIPAA) and can be programmatically tested for usability and quality

LLM Training & Evaluation

Lead generation and delivery of high-quality, scalable datasets focused on SFT, RLHF, reasoning, and agentic workflows

Oversee the entire data lifecycle from client intake and annotation workflow design to delivery

Partner with product, research, and engineering teams to implement evaluation metrics (e.g., win rate, inter-annotator agreement, and pairwise preference scoring)

Client Partnership & Communication

Serve as the primary point of contact for enterprise AI clients; manage expectations, delivery timelines, and escalations

Build relationships with engineering and research stakeholders by delivering consistently high-quality data

Communicate effectively across technical and non-technical audiences; provide transparency through structured updates and quality reporting

Team Development & Tooling

Recruit, mentor, and coach cross-functional leaders (Eng, Data, Ops, and Program Management)

Drive adoption and improvement of internal tools (e.g., task management systems, quality dashboards)

Champion continuous improvement across data quality, tools, and delivery processes

Required Qualifications

10+ years of experience leading large-scale technical delivery organizations, ideally across AI, ML, or data operations

Bachelor's degree in Engineering, Computer Science, or equivalent technical discipline

Demonstrated ability to act as a strategic business partner with our clients, researchers, and engineers at leading LLM labs

Proven success in building and scaling multi-level high performance teams, with distributed global operations

Experience managing managers

Skip-level performance management

Hands-on technical fluency: ability to write and review data validation scripts

Demonstrated experience managing dataset generation or annotation for machine learning model evaluation and/or training

Familiarity with ML tools and data workflows (e.g., HuggingFace, LangChain, Weights & Biases, Databricks)

Preferred Qualifications

Experience evaluating large language model performance and/or improving model performance via fine-tuning

Strong understanding of data quality frameworks, including automation, toolings and manual processes

Experience in AI data annotation, model evaluation, and fine-tuning platforms

Strong communication and storytelling skills with executive stakeholders

Location SF Bay Area (Hybrid) Compensation: $255,000 to $325,000 OTE + Equity