Posted 03 June, 2026
Quality Assurance Engineer II, IN Promotions and Pricing Tech
Amazon
IN, KA, Bengaluru
Full Time
Reference: 71_654242_facdf8c2-c161-4e06-b87e-32c752a1a6e3
IN Promotions & Pricing's mission is to own and redefine key affordability and pricing experiences across the IN Retail marketplace. We're looking for a QAE II who thrives on solving difficult quality problems across distributed services, identifies risks before they reach customers, and brings sharp judgment to every testing decision.
As a QAE II in our team you will grow your QA career by -
- Shaping quality strategy across 6+ distributed services handling billions of INR in promotional value, not just write tests, but decide what a products test guardrails can and cannot be.
- Developing deep systems thinking by owning end-to-end quality for real-time pricing engines, ML-driven matching systems, and will help build for sellers and customers alike.
- Building expertise in core QAE capabilities by driving AI driven initiatives for streamlining performance engineering/load testing strategies.
- Partner directly with SDEs and TPMs influencing architecture and design decisions through quality insights.
- Grow into a quality leader by mentoring peers, establishing quality bars for new services, and driving defect prevention strategies
- Work at the intersection of AI and QA, leveraging and building testing paradigms and tooling while developing critical judgment and leadership.
- You'll own customer trust for key high-traffic promotional and pricing ecosystems, with direct visibility into how your decisions influence daily for hundreds of millions of customers.
Key job responsibilities
- Design and execute test strategies for complex, multi-service systems in pricing and promotional landscape with complex requirements and high ambiguity.
- Build reusable, reliable test automation (integration, load, and performance) for services operating at Amazon India marketplace scale
- Proactively identify quality risks, make trade-offs between test coverage and delivery speed, and influence engineering decisions through data-driven insights.
- Own pipeline health and design automated deployment solutions for production pipelines.
- Partner with SDEs, TPMs, and science teams to validate ML-driven solutions and launch seller/customer facing features.
- Mentor junior QAEs and raise the quality bar for the team through constructive code reviews, test plan reviews, and knowledge sharing. Participate in design reviews, hackathons and other team level activities.
As a QAE II in our team you will grow your QA career by -
- Shaping quality strategy across 6+ distributed services handling billions of INR in promotional value, not just write tests, but decide what a products test guardrails can and cannot be.
- Developing deep systems thinking by owning end-to-end quality for real-time pricing engines, ML-driven matching systems, and will help build for sellers and customers alike.
- Building expertise in core QAE capabilities by driving AI driven initiatives for streamlining performance engineering/load testing strategies.
- Partner directly with SDEs and TPMs influencing architecture and design decisions through quality insights.
- Grow into a quality leader by mentoring peers, establishing quality bars for new services, and driving defect prevention strategies
- Work at the intersection of AI and QA, leveraging and building testing paradigms and tooling while developing critical judgment and leadership.
- You'll own customer trust for key high-traffic promotional and pricing ecosystems, with direct visibility into how your decisions influence daily for hundreds of millions of customers.
Key job responsibilities
- Design and execute test strategies for complex, multi-service systems in pricing and promotional landscape with complex requirements and high ambiguity.
- Build reusable, reliable test automation (integration, load, and performance) for services operating at Amazon India marketplace scale
- Proactively identify quality risks, make trade-offs between test coverage and delivery speed, and influence engineering decisions through data-driven insights.
- Own pipeline health and design automated deployment solutions for production pipelines.
- Partner with SDEs, TPMs, and science teams to validate ML-driven solutions and launch seller/customer facing features.
- Mentor junior QAEs and raise the quality bar for the team through constructive code reviews, test plan reviews, and knowledge sharing. Participate in design reviews, hackathons and other team level activities.
