Manager II Technical Program Management GenAI

About The Role

Uber AI Solutions is an emerging business delivering high-quality, scaled AI data, operations, technology, and analytics programs for leading AI companies. We help frontier labs and AI-native companies build, evaluate, and improve advanced models through a combination of technical program management, operational excellence, data quality systems, and partner capabilities.

We are looking for a TPM Manager to lead the GenAI Foundations team. In this role, you will manage and scale a team of TPMs responsible for delivering complex AI training and evaluation services across coding, software engineering, agentic AI, data analytics, simulation environments, and related domains.

This is a senior, customer-facing leadership role. You will partner closely with Sales, Operations, Product, Engineering, Data Science, Legal, Policy, and external AI lab stakeholders to shape solutions, define delivery models, establish governance, and ensure high-quality execution. The ideal candidate brings strong technical judgment, people leadership experience, deep program delivery expertise, and strong fluency in the AI model training and evaluation ecosystem.

You will be expected to lead from the front: setting vision, building operating mechanisms, mentoring TPMs, engaging directly with customers, and helping UAIS scale differentiated capabilities for frontier AI labs.

• What the Candidate Will Do
  
  

• Build, manage, mentor, and develop a cross functional team responsible for delivering high-complexity AI programs.
• Set clear goals, operating rhythms, standards, and mechanisms for team execution.
• Foster a high-velocity, high-ownership culture grounded in technical depth, structured problem solving, continuous learning, and strong stakeholder management.
• Raise the bar for TPM craft across scoping, planning, execution, communication, risk management, quality tracking, and executive reporting.
  
  

• Partner with Sales and business leaders to engage prospective and existing clients, including frontier AI labs, foundation model companies, AI-native companies, and agentic AI companies.
• Translate ambiguous client needs into clear technical scopes, delivery approaches, governance models, success metrics, and resourcing plans.
• Demonstrate strong credibility with technical client stakeholders by bringing fluency in AI training, evaluation, coding tasks, tool-use workflows, and agentic AI systems.
• Support client discussions around feasibility, tradeoffs, delivery risks, timelines, quality expectations, and operating models.
  
  

• Help define the roadmap for UAIS GenAI technical foundations, tooling, platforms, and delivery capabilities required to support advanced AI training and evaluation programs.
• Partner with Product and Engineering to identify tooling needs that improve delivery velocity, quality, auditability, and scalability.
• Continuously improve governance, delivery maturity, escalation mechanisms, quality systems, and cross-functional ways of working.
• Represent UAIS GenAI and agentic AI capabilities in senior leadership forums, client conversations, and strategic planning discussions.
  
  

• 15+ years of overall experience in technical program management, software engineering, technical operations, or related technical delivery roles.
• 5+ years of experience managing managers and technical program managers
• Demonstrated fluency in GenAI, LLMs, model training, and model evaluation workflows.
• Working knowledge of areas such as SFT, RLHF/RLAIF, preference data, coding evaluations, data labeling, benchmark design, simulation environments, agentic workflows, and quality evaluation.
• Strong ability to understand technical architectures, system constraints, data quality requirements, engineering tradeoffs, and delivery risks.
• Strong written and verbal communication skills, including the ability to communicate clearly with senior executives, technical stakeholders, and cross-functional operators.
• Preferred Qualifications
• Bachelors or Masters degree in Computer Science Engineering or a related field
• Deep knowledge of AI domains including GenAI, agentic AI, LLMs, ML operations, coding agents, evaluation frameworks, and data quality systems.
• Experience working with AI labs, model providers, research teams, data platforms, or AI infrastructure companies.