Data Operations Program Manager

Title: Engineering Program Manager
Location: Seattle or Cupertino
Duration: 12 months
Compensation: $55-75/hr
Work Requirements: US Citizen GC Holders or Authorized to Work in the U.S.

About this Featured Opportunity:
We are looking for an Engineering Program Manager to join the Human-Centered AI (HAI) EPM team supporting their Data Operations team. This role will drive programs at the intersection of data operations data engineering and internal tooling that enable the development and evaluation of Generative AI (GenAI) and machine learning systems. The EPM will partner closely with engineering data operations research and cross-functional teams to define roadmaps prioritize investments improve tooling and workflows and drive complex programs from planning through execution.

The ideal candidate has a strong background in AI/ML domain knowledge ML workflows Human evaluation and annotation technical program management data management data engineering and tooling. They do not need to be a software engineer but should have sufficient technical depth to engage effectively with engineers on system architecture data pipelines APIs technical dependencies and engineering tradeoffs.

The Opportunity for You:

• Drive end-to-end program execution for HAI Data Operations including roadmap development prioritization planning milestone tracking dependency management and risk mitigation.
• Partner with Data Operations and Engineering leadership to build and maintain a clear technical roadmap balancing operational needs tooling investments engineering capacity and broader HAI priorities.
• Lead prioritization across competing data operations and tooling requirements helping teams make clear tradeoffs and focus engineering resources on the highest-impact work.
• Drive programs focused on improving and scaling data management data pipelines data processing and operational tooling supporting AI/ML development and evaluation.
• Partner closely with engineers to define requirements for internal data and developer tooling translating operational needs and pain points into clear technical requirements and execution plans.
• Develop a strong understanding of the teams technical architecture systems APIs data flows and tooling to identify dependencies risks bottlenecks and opportunities for improvement.
• Facilitate technical discussions and architecture reviews ensuring decisions dependencies tradeoffs and follow-up actions are clearly understood and driven to closure.
• Work with engineering teams to improve the reliability scalability efficiency and usability of data operations workflows and supporting platforms.
• Identify opportunities to automate and streamline manual or repetitive data operations processes through improved tooling and workflows.
• Coordinate across engineering research data science and other HAI teams to ensure data and tooling capabilities meet the needs of GenAI development and evaluation programs.
• Establish clear program metrics and mechanisms to measure operational efficiency tooling adoption reliability throughput and overall program health.
• Communicate program status technical risks dependencies tradeoffs and decisions clearly to both technical teams and leadership.
• Create scalable program management processes that improve visibility accountability prioritization and execution across Data Operations.

• 5 years of experience in engineering program management technical program management product management or a related role supporting complex engineering organizations.
  • Demonstrated experience developing and managing technical roadmaps and prioritization frameworks.
  • Proven ability to drive complex cross-functional programs with multiple dependencies and stakeholders.
  • Ability to translate ambiguous operational needs into clear requirements priorities milestones and execution plans.
  • Excellent written and verbal communication skills with the ability to communicate effectively across engineering teams technical leadership and senior stakeholders.
• Familiarity with ML lifecycle and GenAI feature development with particular emphasis on Human evaluation annotation and reinforcement learning with human feedback.
• Experience managing programs involving data platforms data engineering data management data operations or large-scale data processing systems.
  • Strong analytical and problem-solving skills with the ability to use data to inform prioritization and program decisions.
  • Strong technical fluency and demonstrated ability to partner effectively with software and data engineers.
• Ability to understand and participate in discussions involving system architecture data pipelines APIs services technical dependencies and engineering tradeoffs.
  • Familiarity with software development concepts and languages such as Python or Java sufficient to understand engineering discussions and technical designs; hands-on coding experience is not required.
• Experience driving tooling or platform programs particularly internal tools used by engineering data or operations teams.

• Experience supporting AI/ML or Generative AI development evaluation or data programs.
• Understanding of data pipelines ETL/ELT workflows data orchestration dataset management and large-scale data processing.
• Familiarity with technologies such as SQL Spark Airflow Kubernetes cloud data platforms or similar data infrastructure technologies.
• Experience managing internal developer platforms workflow automation data tooling or operational tooling.
• Understanding of the ML data lifecycle including data collection ingestion transformation curation annotation evaluation and monitoring.
• Experience working with human data operations annotation labeling or evaluation workflows.
• Familiarity with APIs distributed systems and service-oriented architectures.
• Experience defining operational metrics SLAs/SLOs dashboards and mechanisms for measuring platform or workflow performance.
• Experience working in a fast-paced environment where priorities evolve based on research product and engineering needs.
• Experience supporting globally distributed engineering and operations teams.

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