Software Engineer II, Associate Experience

Amazon; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Amazon is seeking a Software Engineer to define and build the Associate Context & Insights platform for Customer Service. You will work with senior engineers on end-to-end design, implementation, testing, and deployment of a new product space that enhances associate lifecycle context and enables smarter CS products.

The role emphasizes collaboration with Engineering, Applied Science, BI, UX, Operations, and leadership to deliver scalable solutions that improve customer outcomes and operational

Qualifications

• 3+ years of professional software development experience.
• 2+ years in design or architecture of large software systems.
• Experience programming in Java/C++/C# and OO design.
• Experience delivering production-grade software to customers.
• Knowledge of ML fundamentals, transformer basics is a plus.

Responsibilities

• Define long-term architecture for Associate Context & Insights platform.
• Set engineering excellence standards for the team.
• Deliver minimum viable product increments.
• Influence leadership on investments to improve associate capability and efficiency.

Skills

Software development

Java/C++/C#

OO design

Architectural design

Team collaboration

Problem solving

ML fundamentals

Education

Bachelor's degree in Computer Science

Tools

Git

CI/CD

Cloud deployment

Job description

Amazon Customer Service handles hundreds of millions of customer contacts each year across every Amazon business. Our Associate Experience organization owns the products, platforms, and AI systems that determine how Customer Service Associates (CSAs) onboard, learn, receive coaching, improve performance, and collaborate with AI to deliver exceptional customer outcomes.

As Customer Service evolves, associates will increasingly solve sophisticated customer problems while AI automates routine interactions. This requires fundamentally reimagining how Amazon develops, supports, and continuously improves one of the world’s largest workforces.

We are seeking a Software Engineer to define and build the Associate Context & Insights platform, creating a continuously evolving representation of associates from signals across the associate lifecycle and making that context reusable across CS products.

This SDE will work with other senior engineers to define the architecture for the Associate Context & Insights platform, and own the system end to end from design, implementation, testing, and deployment. The current platform does not exist in the form it needs to, providing a rare opportunity to define an entirely new product space.

This is a highly strategic role requiring close partnership with Engineering, Science, Business Intelligence, UX, Operations, Routing, Workforce Planning, and senior leaders across Customer Service.

Key job responsibilities

• Define the long-term architecture for Associate Context & Insights platform
• Establish engineering excellence standards for the team
• Deliver the minimum viable product incrementally
• Influence senior leadership on long-term investments that improve associate capability, customer outcomes, and operational efficiency.
• Partner closely with Engineering, Applied Science, and Business Intelligence to continuously improve the product

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
• Experience building complex software systems that have been successfully delivered to customers
• Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

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
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques

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