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Technical Program Manager, EHS Data Infrastructure and Analytics

Google
Posted 14 hours ago, valid for 12 days
Location

San Francisco, CA, US

Salary

$192,000 - $278,000 per year

Contract type

Full Time

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Sonic Summary

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  • The position of Technical Program Manager at Google requires a Bachelor's degree in a technical field and a minimum of 8 years of program management experience.
  • Candidates should have 8 years of experience managing cross-functional projects and a proven track record in EHS program management or related fields.
  • The role involves leading the integration and operational adoption of AI/ML technologies in EHS programs, collaborating with various stakeholders to ensure effective implementation.
  • Strong analytical, problem-solving, and communication skills are essential, as the manager will interact with both technical teams and executives.
  • The salary for this position ranges from $192,000 to $278,000, with additional benefits including a 20% bonus target and equity.

Minimum qualifications:

  • Bachelor's degree in a technical field, or equivalent practical experience.
  • 8 years of experience in program management.

Preferred qualifications:

  • 8 years of experience managing cross-functional or cross-team projects.
  • 8 years of experience in EHS program management, project management, or a related field.
  • Proven track record of successfully leading and delivering complex, cross-functional projects.
  • Strong analytical and problem-solving skills.
  • Excellent communication, collaboration, and people management skills, executive presence.

About the job:

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

As an Environmental, Health and Safety (EHS) AI and Innovation Technical Program Manager within the EHS Construction team, you will lead the strategic integration, deployment, and operational adoption of AI/ML technologies across EHS programs. Acting as the critical bridge between EHS operational leaders and Technical Development teams, you will drive the practical utilization of AI within our systems and next-generation mobile hubs. With your leadership, you will directly accelerate the identification, creation and action required to build and deploy AI driven solutions. You will be a planner and a doer, leaning in and experimenting with the endless possibilities offered by AI adoption.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Lead the operational roll-out, training, and user adoption of AI/ML integrations such as predictive safety modeling and automated incident triage to ensure on-site teams actively use these tools for hazard prevention.
  • Partner with development teams to embed intelligent features such as NLP-driven safety alerts and automated compliance scorecards into existing EHS software platforms and mobile reporting hubs.
  • Collaborate closely with EHS site managers and operational stakeholders to identify safety pain points and translate them into clear, actionable requirements for AI development partners.
  • Collaborate with external vendors and industry experts to evaluate and pilot AI technologies, including computer vision for hazard detection or LLMs for safety policy retrieval.
  • Establish feedback loops to continuously monitor, validate, and improve the accuracy of deployed AI models, ensuring they meet strict data privacy and safety governance standards.



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