Software Development Engineer II, Enterprise Engineering

AI in this role

Design and build enterprise data governance platforms with potential application of generative AI for policy enforcement.

slackm365workdocsquipasanapython

software-engineeringdistributed-systemsdata-governanceprivacy

Amazon Enterprise Engineering (EE) builds and operates the internal productivity platforms that Amazon employees rely on: Slack, M365, WorkDocs, Quip, Asana, and Kingpin. The team manages these platforms at Amazon scale and is now building a new layer on top of them, a self-service data governance platform that handles how employee data in these systems is accessed, classified, and audited for legal and privacy purposes. The platform spans the full stack: a consumer-facing request portal, a policy rules engine that treats Legal and Privacy requirements as tested software, a data classification pipeline operating at item level across millions of records, high-scale replication pipelines from source systems into a governed data lake, and a secure analytics environment. This is a greenfield build. The team is small and the problem is large. Engineers own significant surface area, work directly with Legal, Privacy, and Security stakeholders to translate policy requirements into enforcement logic, and build systems that will govern data access for every Amazon employee.

Are you passionate about building software end-to-end? As a Software Development Engineer on this team, you will design, develop, and deliver features that solve real problems in data governance, privacy enforcement, and secure access. You will work across the full software development lifecycle: from understanding the needs of Legal, Privacy, and Security stakeholders to deploying and operating production systems that govern data access for every Amazon employee. This role offers the opportunity to apply Generative AI where it creates real leverage. If you are a self-starter who thrives on turning ambiguous problems into clear, simple solutions, we want to hear from you.

Key job responsibilities
- Design and implement software solutions across the full development lifecycle, including requirements gathering, architecture, coding, testing, deployment, and operational support.
- Write high-quality, maintainable code and actively participate in code reviews, providing constructive feedback to peers and mentoring team members on best practices.
- Identify root causes of operational issues and implement permanent fixes, continuously improving system reliability and performance.
- Collaborate with customers, stakeholders, and cross-functional teams to understand business needs and deliver the right technical solutions that balance short-term priorities with long-term architectural goals.
- Evaluate and integrate new tools and approaches, including generative artificial intelligence capabilities, to improve team productivity and software quality.

About the team
Amazon Enterprise Engineering (EE) builds and operates the internal productivity and collaboration platforms that Amazon employees use every day: Slack, M365, WorkDocs, Quip, Asana, and Kingpin. The team owns both the platforms and the governance frameworks that protect employee data as it moves across those systems.

Basic qualifications

- Bachelor's degree or equivalent
- 3+ years of non-internship professional software development experience

Preferred qualifications

- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems

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

Software Development Engineer II, Enterprise Engineering at Amazon rates 25 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.

●●●● 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.

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

Software EngineeringDistributed SystemsData GovernancePrivacySlackM365WorkdocsQuip

Questions you could be asked

Tell me about a project where software engineering was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where data governance was part of your work. What did you do?
Tell me about a project where privacy was part of your work. What did you do?
Walk me through how you've used Slack in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Software Engineering, Distributed Systems, Data Governance, Privacy, and Slack. 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.

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