Qa Automation Lead

Tekskills Inc.; Delhi; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Tekskills Inc. in Delhi seeks a QA Engineer with strong Python skills and familiarity with Java, to help modernize testing in a complex landscape. You will leverage AI experience to design inventive, useful GenAI or agentic solutions and contribute to automated testing initiatives.

You'll build and run test frameworks within a pipeline, apply SQL to validate data, and tackle legacy manual processes to accelerate AI-powered automation while learning aggressively and delivering rapid results.

Qualifications

• Proficiency in Python for QA testing with Java familiarity as a bonus.
• Experience applying AI/GenAI to testing and automation.
• Ability to build/test frameworks and run in a pipeline.
• Strong SQL skills to validate data and results.
• Able to navigate a large, established landscape and learn quickly.

Responsibilities

• Describe cases where they have stepped in and taken over testing for an area, in this case a specific region/region.
• Work with legacy manual processes to accelerate AI-powered automation.
• Develop and run test frameworks in a pipeline environment.
• Engineer solutions after learning what's needed.

Skills

Python

Java familiarity

AI experience

GenAI

SQL

Test frameworks

CI/CD pipeline

Tools

Test frameworks

CI/CD pipeline

Job description

Role & responsibilities

• QA Engineer strong in python, with Java familiarity a bonus
• AI experience - where relevant and shows inventive & genuinely useful use of GenAI or agentic solutions.
• Experience building test frameworks running on a pipeline.
• Decent SQL skills.
• Especially keen to hear how they have worked in a complex, established landscape - how do they handle it when there is massive amounts to learn and need to get up to speed fast.
• Describe cases where they have stepped in and taken over testing for an area, in this case a specific region/region.
• Good quality engineering talent who isn't afraid to deal with the legacy manual processes to accelerate AI-powered automation process.
• Work hard to learn what's needed and then engineer their way out of problems.