Head of Forward Deployed Engineering

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Company Overview

A technology company focused on AI data development and infrastructure for high-performing and agentic AI systems. The organization combines AI research, data engineering, and human-in-the-loop workflows to develop datasets, benchmarks, evaluations, and custom data solutions for AI research and enterprise applications.

Responsibilities

• Build and lead a Forward Deployed Engineering organization supporting Expert Data-as-a-Service workflows, establishing the team vision, operating model, and scalable delivery processes.
• Build, mentor, and motivate high-performing technical teams while developing the skills, culture, and processes required to consistently deliver high-quality outcomes.
• Own and evolve data pipeline components, including model-assisted labeling, data generation, quality estimation, and data-centric feedback loops that incorporate human input.
• Partner directly with customers, including AI research and engineering teams, to scope complex and novel dataset requirements and translate them into delivery-ready workflows.
• Develop systems for request intake, task orchestration, SLA tracking, and progress monitoring to support reliable execution and prevent delivery gaps.
• Collaborate with research and engineering teams to develop and productionize human-in-the-loop data generation methods, advanced quality techniques, and internal delivery tooling.
• Drive continuous improvement through reusable workflows, operational insights, and scalable processes that improve delivery efficiency while maintaining data quality.
• Lead scoping and presales efforts while working closely with delivery teams and cross-functional stakeholders to establish quality standards and measurement frameworks.
• Define and own workflows and operating processes required to deliver high-quality data at scale.

Qualifications

• 10+ years of experience in applied data engineering, ML engineering, or related technical roles.
• 5+ years of experience leading high-performing technical teams in a hands-on management capacity.
• Demonstrated experience in customer-facing technical roles with strong knowledge of data pipelines and LLM-based workflows.
• Proven experience managing technical field or delivery teams in fast-paced environments with competing priorities.
• Experience as a player-coach, with the ability to remain hands-on while supporting and scaling a technical organization.
• Ability to operate effectively in fast-paced, ambiguous environments involving multiple cross-functional stakeholders.
• Strong practical experience with LLM-based workflows, Python, SQL, and data tooling such as pandas, Plotly, Streamlit, or Dash.

Preferred Qualifications

• Experience with data annotation workflows.
• Experience developing internal tooling for data delivery or data operations organizations.
• Experience designing human-in-the-loop systems and workflows.
• Experience developing quality measurement frameworks and ML-assisted data generation processes.

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