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Sr Product Manager - Tech Integration Lead for Transit Time Authority, Flow Excellence

Amazon is hiring a Sr Product Manager - Tech Integration Lead for Transit Time Authority, Flow Excellence in London, United Kingdom. Level rates it ; you can apply on Amazon.

Level's read on this job

  • Little AI ●○○○ is how Level rates this role: aI is not part of the work.
  • Tools and skills the posting cites include AI safety.
  • Level classifies it as a lead role.
  • Level lists 20,000+ other open roles at Amazon.
  • The role was posted in the last few days.

AI in this role

ai-safety
Every package Amazon delivery depends on an accurate transit time estimate. The Transit Time Authority (TTA) program is the single source of truth that vends those estimates to internal customers across design, scheduling, routing, Amazon Fulfilled Network, and Amazon Freight. As Amazon invests heavily in accelerating same-day and next-day delivery, TTA plays a critical role in making that speed possible. As a Sr Product Manager on this team, you will own the downstream integration of transit-time models into scheduling and routing systems. You will partner with tech and science teams to translate increasingly accurate transit-time data into real operational improvements, driving trade-off decisions between speed, cost, and delivery accuracy that shape how the network performs. This role sits alongside a second Product Manager who owns the upstream model development, giving you a clear scope focused on adoption, system integration, and measurable business outcomes for internal customers across network design, planning, and operations.

Key job responsibilities
- Own the product strategy for integrating transit-time model outputs into downstream scheduling and routing systems, defining requirements and priorities based on business impact and operational data.
- Evaluate technical proposals across ML model design, system integrations, and data pipelines, ensuring trade-off decisions between speed, cost, and delivery accuracy are well-informed and clearly communicated.
- Lead cross-functional delivery with tech, science, and business partners, driving alignment across teams with different priorities and influencing strategic direction.
- Maintain TTA infrastructure for EU. Identify opportunities to apply generative AI tools to accelerate insight generation, automate analytics workflows, and improve team productivity while applying responsible AI practices.
- Define success criteria and performance metrics for transit-time adoption, monitor operational health post-launch and benefits, and drive continuous improvement through data analysis and stakeholder feedback.

A day in the life
You might start your morning reviewing transit-time performance dashboards and flagging anomalies that need investigation. From there, you could join a working session with scheduling and routing engineers to define integration requirements for a new model granularity. After lunch, you prepare a trade-off proposal for business stakeholders, quantifying how a change in transit-time strategy would affect cost and delivery speed. Later, you sync with the science team on an upcoming model update and draft acceptance criteria for the next release.

About the team
The Transit Time Authority team provides the transit-time inputs that power scheduling, routing, and network design across Amazon's middle-mile network. We work directly with North American tech and science teams to improve model accuracy and expand coverage to new business flows. The organization is investing in speed, and our team is a key driver of that effort. Previous team members have grown into Technical Product Management roles based on the depth of technical work here. If you want to solve complex optimization problems with real operational impact, we would welcome you on the team.

Basic qualifications

- Bachelor's degree or equivalent
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience with feature delivery and tradeoffs of a product
- Experience owning technology products
- Experience with product cycles of 6+ months
- Experience in influencing senior leadership through data driven insights

Preferred qualifications

- Experience working across functional teams and senior stakeholders
- Experience in using statistical analysis to identify issues or opportunities for improvement

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

How we rate this

Sr Product Manager - Tech Integration Lead for Transit Time Authority, Flow Excellence at Amazon rates 12 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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