Sr TPM AI-Ready Data & Metrics, Analytics Insights Research Engineering and Science (AiRES)

Amazon is hiring a Sr TPM AI-Ready Data & Metrics, Analytics Insights Research Engineering and Science (AiRES) in Dallas, United States. Level rates it ; you can apply on Amazon.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
The posting mentions Python, SQL and AWS among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.
Posted within the past two weeks.

AI in this role

Lead data engineering and metrics foundation for AI systems and conversational agents at AWS Applied AI Solutions.

PythonSQLAWS

ragnlpdata-engineeringbusiness-intelligencedata-modelingapi

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.

We are building the data and metrics foundation that our AI systems depend on. This role owns the readiness of the data engineering designs, pipeline and the BI Engineering (BI) metrics/semantic layer the trustworthy, well-defined, low-latency source of truth that every AI system consumes to deliver high-quality insights to end users.

You are the owner of the data supply chain for AI: clean, governed, well-modeled, fast-serving data and certified metrics. AI experiences including our conversational insights agent are built directly on the foundation you own. You'll partner closely with the teams building those experiences, giving them the data contracts, certified metrics, and latency guarantees they need to succeed, and closing the data and metric gaps that stand between a good answer and a great one. Your impact shows up everywhere AI touches data: the more reliable, well-defined, and fast your platform, the better every insight our users receive.

Key job responsibilities
Own data engineering readiness pipeline reliability, freshness, schema/data contracts, and the transformation layer that turns raw data into AI-consumable data products.
Own the BI metrics & semantic layer drive consistent, certified metric definitions (single source of truth) so AI systems and dashboards compute the same numbers the same way.
Guarantee high quality, low latency, set and hold SLAs for data freshness, accuracy, completeness, and query/serving latency that AI consumers require for real-time insights.
Define the AI-consumption interface data contracts, certified metric catalogs, retrieval/RAG-ready structures, and APIs the conversational agent (and future AI consumers) build against.
Partner tightly with the conversational-agent team as a primary internal customer; align roadmaps, close data/metric gaps that block agent quality, and establish feedback loops on where the agent's answers fail due to underlying data.
Establish governance metric certification process, data quality monitoring, lineage, and ownership so trust in the platform scales.
Prioritize the roadmap across pipeline modernization, metric coverage, and latency/serving improvements, balancing foundational investment against consumer needs.
Write crisp technical product docs (PRFAQs, one/two-pagers, data-contract specs) and drive alignment across Data Engineering, BI, Science, and the AI-application teams.

A day in the life
As a Technical PM bridging the gap between data and AI, you act as the critical connective tissue translating high-level business goals into scalable data architecture. You collaborate with business stakeholders and AI/ML Scientists to turn abstract requirements into concrete features, training datasets, and real-time data needs. Simultaneously, you partner with Data and BI Engineers to design low-latency feature stores, map data schemas, and standardize the business metrics conversational agents use to make decisions. Your focus remains entirely on building a robust, high-performance data foundation layer, ensuring upstream pipelines seamlessly power downstream AI logic.

About the team
Our team owns the Analytics, BI dashboards, and ML models that drive AWS Support operations across customer experience, operational efficiency, tooling, and security. We act as the strategic bridge within the organization, partnering directly with operations managers, leadership, and central support functions to deeply understand their day-to-day challenges.
From there, our team of AI/ML Scientists, Data Engineers, and BI Engineers translate those requirements into scalable data architectures, robust metrics, and automated systems. Ultimately, we build and maintain the high-performance data solutions that our internal stakeholders rely on to optimize global operations

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic qualifications

- 7+ years of working directly with engineering teams experience
- 5+ years of technical program management working directly with software engineering teams experience
- Experience developing and executing/delivering product and technical roadmaps
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems, or experience in machine learning, data mining, information retrieval, statistics or natural language processing

Preferred qualifications

- 5+ years of project management disciplines including scope, schedule, budget, quality, along with risk and critical path management experience
- Experience managing projects across cross functional teams, building sustainable processes and coordinating release schedules
- Experience defining KPI's/SLA's used to drive multi-million dollar businesses and reporting to senior leadership

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 TPM AI-Ready Data & Metrics, Analytics Insights Research Engineering and Science (AiRES) at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

Sr TPM AI-Ready Data & Metrics, Analytics Insights Research Engineering and Science (AiRES) is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in US, TX, Dallas.
The job was posted on November 2, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGNLPData EngineeringBusiness IntelligenceData ModelingAPIPythonSQL

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where business intelligence was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, NLP, Data Engineering, Business Intelligence, and Data Modeling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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