At a Glance
- Tasks: Lead the quality governance and scaling of AI judges for conversational shopping.
- Company: Join Amazon's innovative Rufus AI team shaping the future of shopping.
- Benefits: Competitive salary, diverse work culture, and opportunities for growth.
- Other info: Dynamic team environment with a focus on measurement and quality.
- Why this job: Make a real impact on AI technology that serves millions globally.
- Qualifications: Experience in product management and technical delivery required.
The predicted salary is between 70000 - 90000 £ per year.
Amazon's Rufus AI team is building the future of conversational shopping. Rufus helps hundreds of millions of customers find and discover products through natural language. Behind every response is an automated quality measurement system powered by LLM-as-a-Judge (LLMAJ) technology.
We are seeking a Sr. Product Manager-Tech to own the quality governance, global scaling, and operational excellence of this judge portfolio. You will work alongside Language Engineers who build and tune judges, Product Managers who define quality criteria and evaluation standards, Data Scientists who operate evaluation pipelines, and Engineering teams that build the infrastructure that runs evaluations. This is a high‑autonomy role: you own your domain end‑to‑end and are expected to drive decisions, not just track workstreams.
This role sits at the intersection of AI evaluation, product management, and applied tooling. You will own the governance framework for a portfolio of dozens of LLM judges that power critical evaluation metrics used for release decisions, competitive benchmarking, and leadership reporting. You will drive the localization of judges from en‑US to 5+ international marketplaces, facilitate model evaluation and debugging workflows, and build purpose‑built tools and agents to automate governance operations at scale.
Key job responsibilities- Own the LLMAJ governance framework: judge registry, versioning standards, quality validation gates, deprecation policies, and agreement rate monitoring across the full judge portfolio.
- Own the international LLMAJ expansion: drive judge localization from en‑US to global marketplaces, identify coverage gaps, define remediation plans, and validate judge quality per locale.
- Facilitate model evaluation and debugging: work with Language Engineers and Scientists to trace response quality issues, inspect production logs, and root‑cause judge disagreements or quality regressions.
- Build purpose‑built tools and agents: code automation using internal agent frameworks to streamline governance workflows, judge monitoring, data extraction, and reporting.
- Define and own partner‑facing quality metrics powered by LLMAJ, including defect rates, agreement rates, and evaluation dimension reporting across partner teams.
- Drive human‑in‑the‑loop validation workflows, coordinating between evaluation platforms and annotation teams to maintain judge calibration.
- Drive discipline on evaluation requests by enforcing data‑driven problem statements, clear scoping, and definition of done before work begins.
- Write business requirements documents, contribute to leadership updates, and represent LLMAJ governance in cross‑functional forums.
A day in the life
You start the morning checking agreement rate dashboards for drift across international locales and triaging alerts. A new prompt release is shipping, so you pull evaluation results, spot two judges regressing in the Japanese marketplace, and open a debugging session with a Language Engineer to trace the root cause. After lunch, you present international judge coverage in a cross‑functional review. In the afternoon, you ship an update to a governance agent you built that auto‑generates weekly judge health reports. You close the day pushing back on an under‑scoped evaluation request.
About The Team
We are the team responsible for measuring whether Amazon's AI shopping assistant is actually good. We build LLM judges, define quality standards, and run evaluations that directly inform what ships to hundreds of millions of customers. Our team includes Language Engineers, Data Scientists, and Product Managers who work closely with Science, Engineering, and Product teams across the organization. We move fast, care deeply about measurement rigor, and believe that if you cannot measure quality automatically, you cannot improve it at scale.
Basic Qualifications- Bachelor's degree
- Experience in technical product management, program management or engineering
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience with feature delivery and tradeoffs of a product
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience representing and advocating for a variety of critical customers and stakeholders during executive‑level prioritization and planning
- Experience in using analytical tools, such as Tableau, Qlikview, QuickSight
- Experience in building and driving adoption of new tools
Senior Product Manager - Tech, GenAI, Amazon Rufus employer: PMs for Hire
At Amazon, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. As a Senior Product Manager in the Rufus AI team, you'll have the opportunity to lead impactful projects that shape the future of conversational shopping while collaborating with talented professionals across various disciplines. Our commitment to employee growth is evident through our robust training programmes and career advancement opportunities, making Amazon an exceptional employer for those seeking meaningful and rewarding work in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Manager - Tech, GenAI, Amazon Rufus
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We think you need these skills to ace Senior Product Manager - Tech, GenAI, Amazon Rufus
Some tips for your application 🫡
Show Off Your Product Passion:When applying for a product management role like Senior Product Manager - Tech, GenAI, Amazon Rufus, let your passion for developing products shine through in your cover letter. Share specific examples of products you've managed, how you solved user needs, and any successful outcomes you've achieved. This is your chance to showcase your understanding of the product lifecycle!
Highlight Your Cross-Functional Skills:Product management isn't just about understanding the product; it’s about collaborating with different teams! Make sure to emphasise your experience working with developers, designers, and marketers. Use your CV to showcase your ability to bridge gaps between these areas, and include relevant experiences that demonstrate your communication and leadership skills!
Include Your Metrics and Achievements:In a full-time product management application, data speaks volumes! Quantify your achievements wherever possible. Did you increase user retention by a certain percentage? Launch a product ahead of schedule? Include these metrics in your CV to paint a picture of your impact and effectiveness in previous roles.
Tailor Your CV to the Role:Make sure your CV is tailored for the Senior Product Manager - Tech, GenAI, Amazon Rufus position at PMs for Hire. Use keywords from the job description and ensure your relevant experiences are front and centre. Highlight any certifications or relevant training you’ve completed that will make you stand out as a strong candidate for the role. And remember, we’re excited to see your application on our website!
How to prepare for a job interview at PMs for Hire
✨Understand the Product Life Cycle
As a product management candidate, we need to get our head around the complete product life cycle. Be prepared to discuss real-world examples of how you’ve managed product development from ideation to launch. Bring specific insights on tools like JIRA or Trello that can help streamline these processes.
✨Showcase Your Cross-Functional Skills
Product management is all about collaboration. We should be ready to highlight how we’ve worked across teams—think marketing, engineering, and design. Prepare to discuss scenarios where you had to mediate differing opinions and how you got everyone on board with a shared vision.
✨Prepare for Case Studies
In a full-time role, we can expect to encounter case study questions during our interviews. Practise solving hypothetical product problems on the spot, such as prioritising features for a new app or improving user engagement metrics. This will show our analytical thinking and decision-making skills.
✨Know Your Metrics
Let’s face it, numbers are our best friends in product management. We should prepare to discuss key performance indicators (KPIs) and how we've used analytics to inform product decisions. Dive into examples where data has driven our strategy for improvements or justified product changes.
