Technical Program Manager, Google Cloud Applied AI

Google Google · Big Tech · Bengaluru, Karnataka, India

This role is for a Technical Program Manager focused on building high-impact AI agents for enterprise clients within Google Cloud. The TPM will elicit business requirements, conduct A/B testing and PoCs, collaborate with Data Science and Engineering on data pipelines for ML models, and ensure solutions address supply chain bottlenecks. They will also manage a team of TPMs, including resource allocation and hiring. The role involves integrating generative AI solutions into business processes and agent-based modeling.

What you'd actually do

  1. Collaborate with team members and stakeholders to understand or identify defined work problems and program goals, obtain prioritized deliverables, and discuss program impact.
  2. Prioritize program goals, understand and translate other stakeholders needs into program goals and prioritized deliverables with minimal assistance, and contribute to decisions on prioritizing goals and deliverables.
  3. Define the scope of projects and develop, execute, or manage project plans for supported programs.
  4. Review key metrics pertaining to a program, monitor potential metric deviations, and define corrective actions for critical deviations.
  5. Identify, communicate, and collaborate with relevant stakeholders within one or more teams to drive impact and work toward mutual goals. Build, maintain and enhance business, operational, and management dashboards.

Skills

Required

  • program management
  • software industry experience
  • Computer Science, Engineering, Mathematics, Operations Research, or related quantitative field
  • technical documentation
  • A/B testing
  • Proof-of-Concept (PoC) experiments

Nice to have

  • cross-functional or cross-team projects
  • classical ML solutions
  • predictive modeling
  • deep learning solutions
  • complex prompt engineering
  • generative AI
  • integrating GenAI solutions into business processes
  • agent-based modeling
  • communication skills
  • translate complex technical concepts into clear business implications

What the JD emphasized

  • build high-impact AI agents
  • architect data pipelines, ensuring information is structured for ML models
  • integrating GenAI solutions into business processes
  • agent-based modeling

Other signals

  • AI agents
  • ML models
  • Data pipelines for ML
  • Generative AI
  • Agent-based modeling