Sr. Manager, Software Development, WW Sustainability
Generate a McCoy IQ challenge in 30 seconds.
See how candidates think and approach the work this role demands, before the phone screen. We'll build a video challenge from this posting, and you can edit or share it before it goes live.
Key details
Why this role is notable
Amazon is treating carbon accounting as production software infrastructure, building an auditable emissions platform that feeds internal planning and is also sold to outside partners and customers as a product.
Job Description
The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable.
Amazon's Worldwide Sustainability team is building the science and technology infrastructure that makes our sustainability commitments real — auditable, automated, and actionable at Amazon's scale. At the center of that infrastructure is the Carbon Intelligence Platform: the system that calculates emissions across Amazon's businesses, powers planning and abatement decision-making, and serves external sustainability products for partners and customers outside Amazon.
We are looking for a Senior Manager, Software Development to lead the engineering team building and operating this platform. This is a player-coach role — you will set technical direction, manage and grow a team of engineers, and stay close enough to the code and architecture to make the hard technical calls yourself. You will own production systems that business unit leaders, finance teams, and external partners depend on for numbers they report publicly and use to make consequential decisions.
This role sits at a distinctive intersection: technical depth and organizational scope at the same time. You will partner with research and sustainability scientists whose methodologies — increasingly AI and ML-enabled — your team implements in production. You will own an external-grade API surface that commercial sustainability products depend on to serve customers outside Amazon. And you will build an AI-native engineering team: one that builds AI/ML systems in production *and* uses AI-assisted development and testing as standard workflow, measuring success by the pace at which new capabilities reach customers reliably.
Your ability to communicate and influence others will be a key to success. You are a results-oriented, customer-focused manager who gets excited about diving deep, running hard, and delivering a big impact.
Key job responsibilities
Carbon Intelligence Systems:
- Every carbon calculation that any Amazon business unit or external partner relies on runs through systems you own and operate
- External-grade API surface consumed by commercial sustainability products — versioned, rate-limited, documented, and reliable at external SLAs
- Assurance & Decision-making: All data must be fully explainable to assurance providers, external stakeholders and enable rapid decision making
- Carbon Facts and Assumptions
Engineering & People Leadership:
- Lead a team of software development engineers directly; this is an level 7 player-coach role with hands-on technical involvement
- Set technical direction and architecture — API design, system reliability, AI/ML production infrastructure, and technical debt management
- Own the engineering operating model: production reliability, incident response, deployment practices, and on-call
- Own model serving infrastructure, inference pipelines, model observability, and automated retraining pipelines
- Drive AI-native engineering practices: AI-assisted development and testing as standard workflow, measured by velocity and reliability of customer-facing delivery
- Hire, develop, and retain strong engineering talent
Science-to-Production Boundary:
- Receive methodology and model specifications from the science team and build the production infrastructure that makes them reliable at scale
- Triage production failures independently and surface systematic patterns back to the science team on a defined cadence Basic Qualifications - Experience partnering with product or program management teams
- Experience managing multiple concurrent programs, projects and development teams in an Agile environment
- Experience building and operating production API platforms at scale — versioning, SLA management, external-grade documentation, and reliability engineering
- Experience building and operating AI/ML production systems — model serving, inference pipelines, drift detection, and retraining automation
- Experience working at the boundary between scientific or analytical systems and production engineering — translating methodology or model specifications into reliable, auditable production systems
- Experience managing external-grade API surfaces consumed by customers or partners outside your organization
- Track record of hiring and developing strong engineers Preferred Qualifications - Experience in sustainability, climate, or environmental domains — familiarity with carbon accounting, emissions calculation, or regulatory reporting
- Experience in environments where calculation lineage, reproducibility, and audit readiness are first-class engineering requirements
- Experience with semantic data validation — systems where data carries domain-specific meaning that determines scientific validity, not just structural conformance
- Experience driving AI-assisted development workflows that improve delivery pace without compromising engineering quality
- Experience building on AWS
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 220,100.00 - 297,700.00 USD annually
Interested in working for companies like this one?
Answer a McCoy challenge. Companies hiring in operations see your response and reach out when they want to talk.
About 15 minutes to prepare and 5 minutes to record. Unlimited retakes and a teleprompter help you answer. No AI training, and you can delete your response anytime.
This isn't an application to Amazon.
Audit details(provenance, verification trail, raw fields)
Core fields
amazon:10590801Provenance
amazonVerification trail
This posting hasn't been probed by our closure verifier yet. Stream C runs on a rolling schedule against postings approaching the close-decision threshold.
LLM enrichment
See how we measure for definitions, or our corrections log for known issues. Found something wrong? Flag a correction.
