Quality Assurance (QA) - Lead - MiDAS

Bosch; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Bosch Global Software Technologies Private Limited in Bengaluru seeks an experienced QA leader to own AI quality strategy and test automation across GenAI and ML-enabled features.

The role focuses on building a dual-layer automation suite (deterministic UI/API tests with Playwright/Pytest and probabilistic evaluation of LLM outputs), embedding checks into GitHub Workflows, and driving performance testing with JMeter to ensure reliability in production.

Qualifications

• 8+ years of Software QA experience.
• Ability to define quality in an ambiguous, non-deterministic AI landscape.
• Bachelor's or Master's in Computer Science, Software Engineering, or a related field.

Responsibilities

• Develop and own evaluation framework for GenAI solutions.
• Architect hybrid test automation with deterministic and probabilistic layers.
• Embed automated quality checks into GitHub Workflows for CI/CD.
• Lead performance testing with JMeter and resilience initiatives.

Skills

Python Mastery

Pytest

Playwright

JMeter

GitHub Actions

AI Quality

GenAI Evaluation

Problem Solving

Learning Agility

Education

Bachelor's or Master's in CS/Software Engineering

Tools

Pytest

Playwright

JMeter

GitHub Actions

Job description

Company Description

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Job Description

Roles & Responsibilities :

AI Quality Strategy: Develop and own the evaluation framework for GenAI solutions, focusing on Faithfulness, Relevancy, and Hallucination detection using LLM-as-a-judge frameworks.

• Hybrid Test Automation: Architect a dual-layered automation suite:

  • Deterministic: E2E UI (Playwright) and API testing (Pytest/Requests).

  • Probabilistic: Automated evaluation of non-deterministic LLM outputs.

• Shift-Left Integration: Embed automated quality checks directly into GitHub Workflows, enabling seamless CI/CD.

Performance & Resilience: Lead JMeter-based performance testing.

Qualifications

Educational qualification:

• Experience: 8+ years in Software QA

• Problem Solving: Ability to define "quality" in an ambiguous, non-deterministic AI landscape.

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

Experience :

• 8+ years in Software QA

Mandatory/requires Skills :

Automation & Tooling

• Python Mastery: Expert-level Python skills for building custom test tooling and automation scripts.

• Testing Stack: Hands‑on proficiency with Pytest (API), Playwright (E2E), and JMeter (Performance).

• DevOps: Advanced experience designing and maintaining GitHub Actions/Workflows for automated test execution.

Core AI & LLM Expertise

• Learning Agility in GenAI: High capability and interest in rapidly mastering AI evaluation concepts. You should be prepared to quickly upskill in automated metrics for LLMs (such as Faithfulness, Relevancy, and Groundedness).

• Exposure to LLM Logic: Basic familiarity with how LLMs function (e.g., prompting, context windows). You should be comfortable exploring and implementing "LLM-as-a-Judge" strategies, where high‑reasoning models help grade application‑specific outputs.

• Orientation toward RAG Systems: Interest in understanding the mechanics of Retrieval‑Augmented Generation (RAG). You will be responsible for defining how we validate the accuracy of data retrieved from our engineering context catalogues and vector databases.

• Data‑Driven Quality Mindset: A strong desire to move beyond binary "Pass/Fail" results toward probabilistic quality monitoring, utilizing tools like Langfuse to analyze live traces and performance trends.

Preferred Skills :

Additional Information

Why Join MiDAS?

You won't just be testing software; you will be defining the quality standards for the future of AI-First Engineering. Your work will directly impact the speed and reliability of vehicle software development globally.