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Director of Quality & Engineering Excellence (AI-Native Commerce Platform)

Fynd -
Mumbai, Maharashtra

Apply Now

Job details

Full-time

Qualifications

BCS
CI/CD
Law
Computer Science
Supply chain
Test automation
Selenium
Git
Information Systems
Java
Master's degree
Microservices
Bachelor's degree
JavaScript
Distributed systems
Continuous integration
GitHub
APIs
Agile
AI
Jenkins
Python

Full job description

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 modern 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.

Apply Now

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