Job 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.
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.
 
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
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.
Posting text © Bosch, shown from its public careers page for reference; the employer's page is the authoritative version. Posted 2026-07-22; listed here until 2026-09-20 unless the employer closes it earlier.
