EngineeringMumbai, IndiaFULL TIMEPosted 4/25/2026

Role Overview

Build and scale an AI-native, automation-first Quality Engineering function that materially improves release velocity, reduces defect leakage, and enables real-time production quality monitoring across the commerce platform. The role is expected to transform quality from a downstream validation activity into an engineering-led quality system embedded across OMS, WMS, storefront, AI copilots, and third-party integrations—ensuring resilient, observable, and trusted customer experiences at scale.

Responsibilities

- Define and execute the long-term Quality Engineering strategy for the commerce and retail platform, with a strong emphasis on automation-first, shift-left, and AI-native testing practices.
- Lead end-to-end quality coverage across OMS, WMS, storefront, AI copilots, APIs, event streams, and integration surfaces, ensuring testability across distributed systems and microservices.
- Build, mentor, and retain a high-performing team of automation engineers and SDETs, setting technical standards and career development plans.
- Design and implement scalable automation frameworks using Playwright, Cypress, Selenium, API testing tools, and programming languages such as JavaScript, Python, or Java.
- Introduce AI-assisted testing capabilities including self-healing test frameworks, intelligent test selection, flaky test detection, and synthetic data generation for commerce scenarios.
- Own quality gates in CI/CD pipelines using GitHub Actions, Jenkins, and related tooling to ensure every release meets agreed standards for coverage, reliability,



and risk reduction.
- Establish robust performance, load, stress, soak, and resilience testing practices using JMeter, k6, Locust, and production-like test environments.
- Define production observability and quality monitoring practices in partnership with platform and SRE teams using Grafana, Prometheus, Datadog, logs, traces, and alerting signals.
- Drive API contract validation, event-driven testing, integration verification, and regression automation for complex distributed commerce workflows.
- Partner with product, engineering, DevOps, and architecture teams to embed quality requirements early in design and development cycles.
- Measure and continuously improve key quality indicators such as automation coverage, defect leakage, escaped production issues, mean time to detect quality regressions, and release cycle duration.
- Champion a culture of engineering excellence, accountability, and continuous improvement, replacing manual-heavy QA practices with up-to-date Quality Engineering principles.

Qualifications

Required

- 10-15+ years of total experience in software quality engineering, test automation, or SDET leadership roles.




- Demonstrated experience leading QA/Quality Engineering transformation in product engineering organizations.
- Strong hands-on coding ability in JavaScript, Python, or Java for building automation frameworks and test utilities.
- Proven experience implementing automation-first testing across web UI, API, integration, and regression layers.
- Experience working with microservices, distributed systems, and event-driven architectures.
- Demonstrated ownership of CI/CD-integrated quality gates and release readiness checks.
- Experience with performance and resilience testing for high-traffic or business-critical platforms.
- Ability to manage and mentor engineers while remaining technically credible and hands-on.
- Comfort working in Mumbai, India, and collaborating with global or multi-functional engineering teams.

Preferred

- Experience in commerce, retail, e-commerce, marketplace, or supply chain technology environments.
- Experience with AI-native testing, LLM-assisted engineering workflows, or self-healing automation frameworks.
- Exposure to observability-driven quality practices using Grafana, Prometheus, Datadog, or similar tools.
- Prior success reducing defect leakage and improving release frequency in platform-led organizations.
- Experience generating and managing synthetic test data for scale, privacy, and scenario coverage.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field preferred; advanced degree is a plus.
- Certifications in testing, cloud, DevOps, or agile quality engineering are a plus, though not mandatory.

📌 Director of Quality & Engineering Excellence (AI-Native Commerce Platform) (India)
🏢 Fynd
📍 India