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Software Development Engineer, Customer Behavior Analytics

Amazon

Software Development Engineer, Customer Behavior Analytics

Amazon

Iasi, ROU

·

On-site

·

Full-time

·

2w ago

Benefits & Perks

Healthcare

401(k)

Equity

Flexible Hours

Mental Health

Parental Leave

Healthcare

401k

Equity

Flexible Hours

Mental Health

Parental Leave

Required Skills

Software development

System design

Architecture

We are hiring SDEs to own the systems of the Agentic Targeting and Traffic Insights team.

Our group is building and operating Amazon’s customer behavior analytics and targeting systems. This team charters is to invent and scale agentic analytics and targeting. You will drive diffusion of AI across our product portfolio.

Our vision is to create an AI-powered content targeting ecosystem where human and AI agents collaborate, driving efficiency across the entire lifecycle including campaign planning, execution, continuous optimization and analytics. We will enable AI agents to operate autonomously or as delegates, safely accessing our service infrastructure and human-centric tools. This will not only boost individual productivity but also unlock new levels of innovation and effectiveness across Amazon. We will also leverage AI to agnatically mine for shopping insights that can be used as a flywheel in driving better business decisions and customer experience.

You will build at scale and focus on ensuring a high bar for the end-customer experience as well as safety, security and data integrity. You will ensure that agentic actions are safe and you will build correctness and accuracy measurements and guardrails.

Basic Qualifications

  • Experience (non-internship) in professional software development
  • Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
  • Experience programming with at least one software programming language

Preferred Qualifications

  • Bachelor's degree in computer science or equivalent
  • Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total / year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge