Senior Program Manager, Tech - Agentic AI
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- Lead execution and shape the product vision for agentic AI data products in partnership with customers, translating emerging client needs into scalable data, evaluation, and delivery solutions.
- Support presales and solutioning by partnering with Sales to engage prospective customers, including AI labs, foundation model companies, agentic AI companies, and other AI-native organizations. You will help define project scope, articulate our capabilities, design delivery and governance models, and bring deep subject matter expertise to client conversations.
- Drive client engagement during program delivery by representing the global service delivery organization, including teams with a significant offshore footprint. You will partner with delivery teams to manage ongoing governance, troubleshoot execution risks, identify upsell and cross-sell opportunities, and bring thought leadership to customer relationships.
- Support program delivery for US/onshore annotation, training, and evaluation programs across AI, LLM, ML, coding, engineering, and data analytics use cases, where required.
- Bring innovation and thought leadership across coding, data analytics, AI training, model evaluation, and agentic AI workflows. You will help identify new opportunities, support model performance benchmarking discussions, and shape the next generation of technical AI data products.
- Advance sourcing strategy by partnering with the Supply team to build and scale US/onshore expert worker pools with the technical expertise required for coding, engineering, data analytics, and AI evaluation programs.
- Inform product and platform roadmap priorities by collaborating with Product and Engineering teams on the tooling, workflow, quality, and platform capabilities required to support coding and data analytics tasking at scale.
- Represent our capabilities with senior stakeholders by evangelizing our coding, data analytics, and AI training/evaluation offerings in leadership forums, customer discussions, and strategic planning conversations.
- Improve delivery maturity and best practices by continuously enhancing ways of working, governance models, quality processes, escalation paths, and operating mechanisms to increase impact, scalability, and client trust.
---- Basic Qualifications ----
- 10+ years of professional experience across software engineering, ML engineering, MLOps, AI data services, technical program management, or related domains.
- Experience leading client-facing engagements with AI labs, foundation model companies, agentic AI companies, or enterprise AI teams, particularly in areas such as data annotation, AI training, model evaluation, performance benchmarking, coding, and software development workflows.
- Strong understanding of AI/LLM training and evaluation workflows, especially for coding and engineering use cases. Familiarity with data analytics, ML, and agentic AI workflows is a strong plus.
- Experience in service delivery management, solutioning, and governance with external client stakeholders, including senior leaders and technical AI teams.
- Familiarity with delivery models, quality control processes, and evaluation methodologies for technical AI data programs, including annotation, training, evaluation, and benchmarking workflows.
- Track record of driving innovation and thought leadership in AI, ML, or LLM training and evaluation services, including identifying new opportunities, shaping client solutions, or developing capabilities based on emerging industry trends.
- Strong executive communication skills, with the ability to bring clarity, structure, and precision to messaging for senior management, clients, and cross-functional teams.
- Excellent collaboration and influencing skills, with demonstrated ability to work across functions, organizational silos, and global teams to drive outcomes.
- Ability to operate effectively in a global organization, working across locations, cultures, and time zones.
---- Preferred Qualifications ----
- Bachelor’s or Master’s degree in Computer Science Engineering or a related field
- Experience in GenAI, agentic AI, LLMs, human-in-the-loop operations, coding agents, evaluation frameworks, and data quality systems.
- Experience working with AI labs, model providers, research teams, data platforms, or AI infrastructure companies.
- Strong business acumen, willingness to take smart risks and grow
For New York, NY-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$150,000 per year - USD$167,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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