Sr. Applied Scientist - AWS Catalog, AWS Catalog

AI in this role

Senior Applied Scientist designing formal permissions models and automated reasoning systems for AWS data security and governance.

tensorflowscikit-learnllms

applied-scienceformal-methodsprogramming-languagesautomated-reasoningdata-security

This is a chance to work at the front of data security and governance with Amazon scale impact on customers. As a Sr. Applied Scientist III, you bring your education, experience, and expertise in formal methods, programming languages, and automated reasoning to the permissions model behind AWS's data catalog, so that customers can state precisely who may see which data and trust that the answer holds wherever that data is read. Experience with LLMs, multi-agent workflows, and structured guardrails that raise determinism in LLM output is a plus. In this role you join a strong group of applied scientists in a highly supportive environment with real cognitive safety and room to grow.

Key job responsibilities
You combine deep expertise in programming languages and automated reasoning to design the language and the formal semantics customers use to express permissions over catalog resources, down to the level of individual columns and rows. The model has to stay correct, compact, expressive enough for real customer intent, explainable when it denies a request, and exhaustively testable. Much of the difficulty is navigating ambiguity to balance those properties against each other. You write clear narratives and documentation that enumerate the design choices and build consensus quickly.

You lead design and delivery of scientifically complex components that are rarely revisited once shipped and that deliver measurable customer benefit. The problems are concrete: proving that a change to a policy cannot expand access beyond what the author intended, deciding whether two policies written in different models grant the same thing, showing that a fast evaluation path on the request hot path agrees with the reference semantics, and keeping permissions faithful to intent as schemas and data evolve underneath them. You maintain detailed knowledge of your team's systems and proactively drive improvements in efficiency and consistency across team boundaries.

You influence your team's science and business strategy, collaborating with Applied Scientists, Engineers, and Product Managers across identity, storage, analytics, and machine learning teams, and contributing to roadmaps, goals, and priorities. You harmonize discordant views and build consensus through thoughtful feedback. Beyond your team, you apply advanced techniques to bottleneck problems and are regarded as a reliable, creative problem solver. You further AWS's academic influence through publications, talks, and advancing the state of the art in data security, governance, programming languages, and automated reasoning.

About the team
The team owns the permissions layer of AWS's data catalog. That covers 1/ the model and formal semantics customers use to author permissions across catalogs, databases, tables, columns, and rows, 2/ the evaluation path that turns those permissions into an authorization decision on every request, under latency budgets that leave no room for a slow answer, 3/ the detection and resolution of divergence between what a customer intended and what is actually enforced as resources change over time, and 4/ converging existing permission models onto one, including the reasoning needed to show that a migration preserves a customer's access boundaries. The team works closely with identity, storage, and analytics teams across AWS.

Basic qualifications

- 6+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

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. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 195,900.00 - 327,200.00 CAD annually

How we rate this

Sr. Applied Scientist - AWS Catalog, AWS Catalog at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● 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. Open the description and count.

Key facts

Sr. Applied Scientist - AWS Catalog, AWS Catalog is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is CAD 196k-CAD 327k a year.
The role is based in CA, BC, Vancouver.
The job was posted on October 1, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Applied ScienceFormal MethodsProgramming LanguagesAutomated ReasoningData SecurityTensorFlowscikit-learnLLMs

Questions you could be asked

Tell me about a project where applied science was part of your work. What did you do?
Tell me about a project where formal methods was part of your work. What did you do?
Tell me about a project where programming languages was part of your work. What did you do?
Tell me about a project where automated reasoning was part of your work. What did you do?
Tell me about a project where data security was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Applied Science, Formal Methods, Programming Languages, Automated Reasoning, and Data Security. 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.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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