AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.
You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety, environment and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
For over 15 years, Amazon Web Services (AWS) has been the world’s most comprehensive and broadly adopted cloud computing platform. What is cloud computing? Cloud computing is the on-demand delivery of IT resources over the Internet.
In 2019, Amazon announced The Climate Pledge, which includes our commitment to power our operations with 100% renewable energy by 2025, on the path to achieving net zero carbon across our businesses by 2040. To learn more about AWS, visit https://aws.amazon.com and https://sustainability.aboutamazon.com/environment/the-cloud.
Amazon is looking for a talented and self-motivated Environmental Digital Solutions Engineer to support the AWS Environmental global programs team. The successful candidate will join the AWS Environmental team, an expanding and dynamic team that is critical to enabling AWS's growth around the world, as well as ensuring regulatory compliance and highest-level environmental performance of AWS's data center global operations. The Environmental team has responsibility for managing Environmental requirements and risk from site selection through to decommissioning. This role requires a highly skilled professional to manage complex, ambiguous audit initiatives across organizational boundaries.
The ideal candidate must lead on AI enhancements and technologies and be strong in data analytic capabilities, influence stakeholders, and work independently while seeking guidance when needed. Strong strategic and tactical skills are essential, including balancing short and long-term needs, mitigating risks, and delivering simplified solutions. Excellent communication skills are crucial, with the ability to present to senior leadership and write strategic narratives. The role involves mentoring, recruitment, and process improvement. Cross-functional collaboration and consensus-building are key. A commitment to diversity, equity, and inclusion is vital, focusing on challenging the status quo and creating inclusive products. The successful candidate will significantly impact long-term organizational goals and model best practices in their domain, driving change and innovation across the organization.




Key job responsibilities
Leadership and AI Driven Environmental Management: Drive innovation in environmental compliance through the application of AI technologies and analytical methods. Design and develop AI-powered compliance monitoring systems using machine learning and advanced analytics for environmental metrics including air quality, water discharge, waste management, and chemical handling
Environmental performance evaluation: Build and implement predictive analytics models to forecast potential environmental regulatory compliance violations and automate risk assessment processes. Create intelligent data pipelines and real-time monitoring dashboards to transform environmental compliance data into actionable insights. Maintain and enhance analytical models while ensuring scalability and performance
Implementation and operation: Lead the integration of AI/ML solutions with existing EHS software systems and data architectures. Collaborate with stakeholders to translate complex business requirements into AI-driven solutions. Develop and optimize machine learning algorithms for automated reporting and compliance pattern recognition
Continual improvement: Drive ongoing scalable improvement of our digital tools and systems to meet business, customer, stakeholder and partner needs.