Qa Automation Lead

Bounteous; Gurugram District, Bengaluru; Hybrid; INR 1,200,000 - 2,000,000; Full time

Job summary

Bounteous is seeking a Senior QA Automation Engineer who treats AI as a core part of quality. You will design and evolve automation across UI, API, mobile, and integration layers, embedding checks into CI/CD for fast feedback.

Lead shift-left initiatives, handle AI-driven testing, and ensure robust testing for AI/ML features with measurable ROI. The role requires 8–10 years in QA/test automation, with 3+ years in a senior/lead capacity, and hands-on experience with modern tools and cloud

Qualifications

• 8–10 years in QA/test automation with at least 3 years in a senior/lead role.
• Proven track record building automation frameworks from scratch and scaling them across teams.
• Strong programming in Python, Java, or TypeScript/JavaScript.

Responsibilities

• Design, build, and evolve scalable test automation frameworks across UI, API, mobile, and integration layers.
• Embed automated quality checks into CI/CD pipelines with fast feedback loops.
• Drive shift-left practices and partner with developers on testability and contract testing.
• Test AI/ML-powered features and evaluate AI testing tools for ROI.

Skills

Python

Java

TypeScript/JavaScript

Playwright

Cypress

Selenium

Appium

REST

GraphQL

gRPC

CI/CD

GitHub Actions

GitLab CI

Jenkins

Azure DevOps

Docker

Kubernetes

AWS

Azure

GCP

SQL

Performance testing

Security testing

Accessibility testing

AI coding assistants

LLM APIs

prompting

Tools

Playwright

Cypress

Selenium

Appium

Postman

REST Assured

Pact

GitHub Actions

GitLab CI

Jenkins

Azure DevOps

Docker

Kubernetes

AWS

Azure

GCP

Job description

About the Role

Were looking for a Senior QA Automation Engineer who treats AI as a core part of how quality gets built, not an add-on.

Key Responsibilities

Automation Strategy & Architecture

• Design, build, and evolve scalable test automation frameworks across UI, API, mobile, and integration layers
• Define the test pyramid and quality gates for the organization, balancing speed, coverage, and reliability
• Embed automated quality checks into CI/CD pipelines with fast, trustworthy feedback loops
• Drive shift-left practices: partner with developers on testability, contract testing, and early validation

AI-Native Quality Engineering

• Use LLMs and AI coding assistants to generate test cases, test data, and automation scripts from requirements, user stories, and code changes
• Implement self-healing locators and AI-assisted test maintenance to reduce flakiness and upkeep cost
• Apply AI to triage failures, cluster defects, detect flaky tests, and identify root causes from logs and traces
• Build or integrate AI agents for exploratory testing, visual validation, and regression selection (risk-based test prioritization)
• Evaluate AI testing tools critically, deciding what to adopt, build, or avoid, and measure their actual ROI

Testing AI/ML-Powered Features

• Build golden datasets, regression suites, and automated evals for prompts, RAG pipelines, and agent workflows
• Test non-deterministic behavior using statistical thresholds, LLM-as-judge techniques, and human review loops
• Perform adversarial testing, including prompt injection, jailbreaks, and data leakage scenarios

Required Qualifications

Experience

• 8–10 years in QA/test automation, with at least 3 years in a senior or lead capacity
• Proven track record building automation frameworks from scratch and scaling them across teams

Technical Skills

• Strong programming ability in at least one of: Python, Java, TypeScript/JavaScript
• Hands-on with modern automation tools: Playwright, Cypress, Selenium, Appium
• API and service testing: REST, GraphQL, gRPC (Postman, REST Assured, Pact, or similar)
• CI/CD experience: GitHub Actions, GitLab CI, Jenkins, or Azure DevOps
• Familiarity with containers, cloud environments (AWS/Azure/GCP), and infrastructure basics
• Solid understanding of performance, security, and accessibility testing fundamentals
• Strong SQL and data validation skills

AI-Native Skills

• Daily, fluent use of AI coding assistants (e.g., Claude, Copilot, Cursor) with strong prompting and output-verification habits
• Experience building workflows with LLM APIs, agents, or MCP-based tooling for testing tasks
• Understanding of LLM limitations: hallucination, non-determinism, context constraints, and data privacy risks

Preferred Qualifications

• Experience testing RAG systems, chatbots, or agentic applications in production
• Background in observability and test analytics (Datadog, Grafana, ELK)
• Experience with visual regression and AI-based visual testing tools
• Knowledge of responsible AI, governance, and compliance considerations
• Contributions to open-source testing tools or internal developer platforms
• ISTQB or relevant cloud/AI certifications

Soft Skills

• Sharp analytical thinking and healthy skepticism toward both code and AI output
• Clear communication with technical and non-technical stakeholders
• Ownership mindset and comfort with ambiguity in a fast-changing tooling landscape
• Curiosity and a bias toward experimentation, with the discipline to measure results