Level

Amazon

Applied Scientist III, AWS Account Management and Governance

Amazon is hiring an Applied Scientist III, AWS Account Management and Governance in Santa Clara, United States. It pays $192k-$260k a year and Level rates it ; you can apply on Level.

AI in this role

Lead the technical vision and development of an AI-based governance intelligence platform utilizing multi-agent LLM frameworks.

tensorflowscikit-learnpythonllm-frameworks
ai-agentsmachine-learninggovernancecloud-computingtechnical-leadership

We are seeking an Applied Scientist III to own the technical vision and development of an AI-based governance intelligence platform that will redefine how account and organizational governance is defined, validated, and enforced at scale. This mission-critical platform will leverage AI-driven autonomous agents to conduct proactive, intelligent governance operations across the account lifecycle.
The platform will integrate deeply with organizational management, identity, and cloud-native control systems to provide self-serve, automated governance insights, policy verification, and enforcement mechanisms. The Governance Foundations team is building a unified governance foundation that consolidates account management controls — including automated enrollment, managed policies, and account lifecycle guardrails — into a single, intelligent, scalable system.
As a senior science leader on the team, you will operate with a high degree of autonomy on ambiguous, open-ended problems that span multiple organizations. You will set the multi-year scientific direction, make the architectural and modeling decisions that others build on, and drive alignment across applied science, engineering, product, and partner teams — up to and including senior leadership. This is an opportunity to shape the future of AI-driven governance assurance at enterprise scale: defining standards, influencing company-wide account governance posture, and leading technical innovation at the highest level.
Key job responsibilities

- Own and define the next-generation governance intelligence and policy-matching platform, setting the multi-year technical strategy for AI-driven governance automation across applied science and engineering teams and resolving the hardest, most ambiguous problems in the space.
- Build on and advance a multi-agent LLM framework for autonomous governance operations, and influence partner organizations to adopt the most promising approaches — including human-in-the-loop enforcement boundaries that cannot be bypassed by autonomous agents.
- Develop a highly scalable intelligent governance agent framework — combining traditional ML and LLM-based techniques — that enables internal teams to automate validation, classification, and enforcement across structured and unstructured policy and account data.
- Provide technical leadership and scientific mentorship across the broader organization — raising the bar on science quality, growing other scientists and engineers, and representing the team's technical direction to senior leadership — while still diving deep hands-on to diagnose complex system performance and correctness problems in distributed governance control planes.
- Define the scientific metrics, evaluation methodology, and quality bar by which the platform's governance decisions are measured and trusted.


About the team

The Accounts Management and Governance team builds the unified governance foundation for account and organizational management at scale. The team consolidates account lifecycle controls, policy propagation, and enforcement guardrails into a single intelligent system, ensuring the experiences Amazon delivers to its customers uphold our highest standards of security, correctness, and operational integrity. The science team harnesses AI to strengthen Amazon's governance posture more efficiently and effectively


Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Santa Clara - 192,200.00 - 260,000.00 USD annually

How we rate this

Applied Scientist III, AWS Account Management and Governance at Amazon rates 95 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.

  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. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsMachine learningGovernanceCloud ComputingTechnical LeadershipTensorFlowscikit-learnPython

Pay

This job starts at
$192k
Typical applied scientist job
$167k

This posting starts 15% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where governance was part of your work. What did you do?
  4. Tell me about a project where cloud computing was part of your work. What did you do?
  5. Tell me about a project where technical leadership was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Machine learning, Governance, Cloud Computing, and Technical Leadership. 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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