Python QA (Gen AI OR Agentic AI)

Michael Page; Mumbai, Pune District; Hybrid; INR 1,500,000 - 1,900,000; Full time

Job summary

Michael Page is seeking a QA Python professional specializing in GenAI/Agentic AI for a leading banking project. This long-term contract spans four years, targeting candidates who blend test automation with AI-powered approaches.

The ideal candidate demonstrates GenAI experience, builds scalable test frameworks, and has solid SQL skills to navigate a complex legacy landscape while accelerating automation.

Qualifications

• AI experience with GenAI or agentic solutions.
• Experience building test frameworks on a pipeline.
• Decent SQL skills.
• Ability to learn quickly in a large, established landscape.
• Experience taking over testing for a regional area.
• Strong engineering mindset to accelerate AI-powered automation.
• Willingness to engineer solutions after learning needs.

Responsibilities

• QA Python work for banking project with GenAI/Agentic AI.
• Project is for a leading Bank.
• Long-term engagement spanning 4 years.

Skills

GenAI/Agentic AI

Test framework development

SQL skills

Learning fast in complex landscapes

Test ownership (regional)

Quality engineering mindset

Problem-solving for automation

Job description

Role & responsibilities

QA Python with GEN AI or Agentic AI

Project is of a leading Bank.

Long term Contract (4 years)

Preferred candidate profile

• 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.