QA Lead/Sr. SDET

StatusNeo is a global AI-native transformation firm helping enterprises design, engineer, and govern AI-led systems with trust at the core.
We work with global enterprises across BFSI, retail, healthcare, airlines, and platform-driven industries to transform how software is built, operated, and scaled in an AI-first world.
Our work is anchored in Authentic AI™ — an approach that treats AI not as a feature or experiment, but as a continuously evolving system that must be engineered with intent, accountability, and governance.
At StatusNeo, we don’t just talk about AI transformation.
We build it — across engineering platforms, AI-native SDLC, agentic systems, and enterprise operating models.

Role Overview

StatusNeo is seeking a Lead/SDET with
AI Automation expertise to drive Quality Engineering initiatives across
enterprise applications, digital platforms, APIs, cloud-native services, and
AI-powered solutions.

The ideal candidate will bring
strong experience in test automation, framework development, AI-driven testing,
and quality leadership. This role will be responsible for defining test
strategy, building scalable automation frameworks, validating AI-enabled
applications, and driving continuous quality practices within Agile and DevOps
environments.

Key Responsibilities

Quality Engineering &
Leadership

Lead QA and automation teams,
providing technical guidance and mentorship.

Define and implement test
strategies, quality standards, and governance processes.

Collaborate with Product,
Engineering, DevOps, and ML teams to ensure quality throughout the SDLC.

Track and report quality metrics,
risks, and release readiness.

Test Automation

Design and develop scalable
automation frameworks using Python, Java, or TypeScript.

Build automated test suites for
UI, API, backend, integration, and end-to-end testing.

Integrate automation into CI/CD
pipelines using Jenkins, GitHub Actions, or Azure DevOps.

Drive Shift-Left Testing and
Continuous Quality Engineering practices.

AI-Driven Testing &
Validation

Leverage AI/LLM tools to
accelerate test creation, maintenance, and optimization.

Implement AI-powered
capabilities such as:

Automated test generation

Self-healing scripts

Test data generation

Defect prediction and analysis

Validate AI/ML applications by
testing:

Accuracy and relevance

Hallucinations and bias

Model inference and ranking behavior

Adversarial and edge-case scenarios

Required Qualifications

Technical Skills

Programming: Python, Java,
TypeScript/JavaScript

Automation: Playwright, Selenium,
Cypress, Appium, PyTest, REST Assured

API Testing: Postman, REST Assured

CI/CD: Jenkins, GitHub Actions,
Azure DevOps

Cloud & Containers:
AWS/Azure/GCP, Docker

Test Management: Jira, Azure
DevOps, TestRail

AI & Emerging Technologies

Experience using AI-assisted
development and testing tools such as GitHub Copilot, Microsoft Copilot,
ChatGPT, ACCELQ, Mabl, Testim, or Functionize.

Understanding of Generative AI,
LLMs, Prompt Engineering, and AI evaluation frameworks.

Experience testing AI-powered
applications and machine learning workflows is highly preferred.