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Senior QA Automation Engineer – AI /ML /Gen AI | On-site, Bangalore

Ntst · Bengaluru, India

How to use this kit

Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.

Interview prep

Be ready to walk through automation architecture choices, how you validate AI/ML features (golden sets, eval harnesses, non-determinism), and on-site collaboration habits. Prepare concrete examples of reducing escape defects and scaling suites for complex products.

Fit summary

Best fit for senior automation engineers who want on-site work in Bengaluru on AI/ML/Gen AI quality—not pure manual QA or fully remote roles.

Day in the role

As a Senior QA Automation Engineer focused on AI/ML/Gen AI on-site in Bengaluru, a typical day centers on designing and maintaining automated tests for ML-backed features, reviewing model-facing flows for regressions, and partnering with engineering on release quality. Expect hands-on work with test frameworks, CI pipelines, and defect triage rather than remote-only collaboration.

Skills to emphasize

Strengthen automation foundations (API/UI frameworks, CI/CD, flaky-test control) and AI-adjacent QA practices: evaluating GenAI outputs, data/contract checks, and performance/reliability around model services. No certification resources were provided for this listing.

FAQ from this listing

Is this role remote?

No. The listing is on-site in Bengaluru, India (remote flag is off).

What is the focus of the QA work?

Senior-level test automation with an AI/ML/Gen AI product emphasis, not generalist manual testing alone.

What company detail is confirmed here?

The employer is given as Ntst with domain ntst.com; further employer facts were not supplied in the source data.

Company facts (cached)

Website: ntst.com

Public cache only — not an employee review.

Role overview (listing rewrite)

Ntst is seeking a Senior QA Automation Engineer - AI /ML /Gen AI | On-site, Bangalore to join its full-time team in Bengaluru, India. This on-site opportunity centres on building reliable automation pipelines that safeguard the accuracy and performance of artificial intelligence, machine learning and generative AI systems for candidates searching Senior QA Automation Engineer - AI /ML /Gen AI | On-site, Bangalore jobs in Bengaluru, India or Ntst careers near me. Role Overview In the Senior QA Automation Engineer - AI /ML /Gen AI | On-site, Bangalore post at Ntst in Bengaluru, India you will own the end-to-end quality strategy for complex AI and GenAI products. Working fully on-site you will design scalable test automation, validate model behaviour under real-world conditions and embed quality gates into every stage of delivery so that AI-driven features ship with confidence and consistency. Responsibilities Create and maintain comprehensive automation frameworks specifically for AI, machine-learning pipelines and generative AI applications. Build reusable test suites that cover data integrity, model accuracy, prompt evaluation, bias detection and output consistency. Integrate automated checks into continuous-integration and continuous-delivery pipelines so regressions are caught early. Partner with data scientists, engineers and product owners to define acceptance criteria that reflect real AI system risks. Execute performance, load and chaos tests tailored to the unique resource patterns of large language models and ML inference services. Analyse detailed test reports, root-cause defects, and drive permanent preventive actions across the AI development lifecycle. Coach junior quality engineers on modern AI testing techniques and automation best practices inside the Bengaluru team. What You Bring Proven senior-level experience delivering QA automation for AI, machine-learning or generative AI systems. Hands-on mastery of common automation libraries and languages such as Python, Selenium, Pytest or equivalent frameworks adapted for model testing. Solid understanding of model validation metrics, data-quality checks, hallucination detection and ethical AI testing practices. Familiarity with CI/CD tooling, containerised environments and cloud-based test infrastructure used by AI teams. Ability to design both functional and non-functional test strategies that scale with growing model complexity. Strong analytical mindset, clear communication skills and readiness to collaborate on-site every day…

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Questions to ask them

Generated for personal interview prep · 2026-07-17 UTC · getajob.ai