- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Reston, VA, USA; Atlanta, GA, USA; Addison, TX, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.
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.
