Technical Program Lead (AI Delivery)

TL;DR

Technical Program Lead (AI Delivery): Managing complex AI data programs end-to-end, from scoping and data design through delivery and quality assurance with an accent on LLM and Gen AI workflows. Focus on building data pipelines, debugging technical issues, and maintaining high-level stakeholder relationships to ensure program success.

Location: Must be based in San Francisco (Hybrid)

Company

hirify.global is a platform providing end-to-end solutions for AI data programs, focusing on high-quality data annotation and management.

What you will do

• Lead LLM and Gen AI data engagements from initial scoping to final delivery.
• Act as the primary technical point of contact for client researchers and engineering stakeholders.
• Write Python and SQL to inspect data, debug pipelines, and automate QA processes.
• Architect data pipelines, quality frameworks, and review infrastructure for scalable execution.
• Manage timelines, staffing plans, and operational discipline across multiple concurrent projects.
• Recruit, mentor, and performance-manage operations and subject matter expert teams.

Requirements

• 4+ years of experience running complex technical projects or operations in client-facing roles.
• Experience in a high-growth startup environment is required.
• Solid coding ability in Python or SQL for debugging and analysis.
• Depth in machine learning, statistics, or data science applied to real-world problems.
• Strong communication skills capable of representing complex technical projects to senior stakeholders like CTOs or VPs.
• Working knowledge of the Gen AI landscape, including LLM training and evaluation.

Nice to have

• Experience managing large distributed contributor or expert workforces.
• Background in management consulting, investment banking, or data-intensive technical services.
• MBA or equivalent advanced degree.

Culture & Benefits

• Opportunity to work at the intersection of customer delivery, systems design, and AI model quality.
• Collaborative environment working directly with researchers and engineering teams.
• Focus on operational ownership and meaningful impact on large-scale AI programs.