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Software Development Engineer, Automated Profitability Management

Amazon

Software Development Engineer, Automated Profitability Management

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

4w ago

Required skills

Machine Learning

The Automated Profitability Management (APM) team is working to reimagine how Amazon Retail manages profitability by combining Machine Learning and Software Engineering. We're building systems that help streamline negotiations with thousands of suppliers around the world — work that touches millions of products across many countries.

In the past, this work meant retail business teams would connect directly with suppliers to discuss and refine the terms of our partnerships. Today, we're scaling that effort across tens of thousands of suppliers, tens of millions of products, and dozens of countries — all while the business continues to grow rapidly. We're evolving retail profitability management from an art into a science, and we're looking for a talented Software Development Engineer to help us build the technology that powers this transformation.

An ideal candidate will partner with Product Managers and Applied Scientists to understand business context, translate business needs into technical solutions, and design distributed systems, ML-driven automation tools, and scalable APIs that support profitability decisions across Amazon's global retail operations. This is a role where you'll have meaningful ownership and the opportunity to see your work make a real difference to the business.

  • Key job responsibilities
  • Drive delivery of high-impact changes that meaningfully improve customer experience and business outcomes at scale
  • Champion engineering excellence across the full software development lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operational best practices
  • Demonstrate exceptional debugging, troubleshooting, and problem-solving skills to resolve complex technical challenges with speed and precision
  • Design and build robust distributed systems and enterprise-scale architectures that meet demanding reliability and performance requirements
  • Partner cross-functionally with teams to define, align on, and deliver strategic technical initiatives
  • Invest in the growth of junior engineers through mentorship, technical guidance, and hands-on coaching — raising the overall effectiveness and productivity of the team

About the team
At Automated Profitability Management (APM), we take pride in being a diverse team, and provide opportunity to demonstrate unique strength that each of us bring to the table. We are a high performing team and give importance to work-life-balance and career growth.
We collaborate with several key teams across Retail world (SCOT, Econ Tech, etc.) on a day-to-day basis. Our customers are retail vendors, vendor managers and retail page customers.

Basic Qualifications

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language

Preferred Qualifications

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience in defining and creating benchmarks for assessing GenAI model performance
  • Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

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. 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, WA, Seattle - 143,700.00 - 194,400.00 USD annually

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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

$1.5T

Valuation

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

4 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total per 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