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Bosch GroupVerified

Extracurricular Internship – DevOps & GenAI Engineer for Quality (f/m/div.)

Region
🌐 Other
Work mode
On-site
Category
QA/SDET
Level
Student/Intern
Data ScienceGenerative AILLMsMicroservicesPython
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About the company & role

Your contribution to something big: As a Quality GenAI Engineer, you design, prototype, and implement AI agents that support engineering workflows across Bosch. You translate complex engineering use cases into intelligent, reliable, and compliant GenAI solutions that accelerate innovation. - Identify opportunities where Generative AI and Agentic AI can drive impact on Quality Engineering standards, tools and corresponding data analysis of manufacturing Quality. - Designing and implementing GenAI agents that support Quality Engineering tasks such as requirements analysis, data and documentation assistance, test interpretation, and failure analysis. - Building AI pipelines using LLMs, embeddings, vector databases, and domain specific knowledge sources. - Integrating AI agents with engineering tools, databases, and repositories (e.g., PLM systems, test data platforms, document repositories). - Developing Retrieval Augmented Generation (RAG) pipelines for structured and semi structured engineering data. - Ensuring agent reliability, traceability, and safe behavior in regulated engineering environments. - Collaborating with domain experts to evaluate usability, performance, and fit for purpose. - Documenting architectures, APIs, integration points, and operational guidelines. - Working closely with security and compliance teams to ensure responsible and compliant AI usage. What distinguishes you: Education - Degree in Computer Science, Engineering, Data Science, or a comparable field. Experience - Experience in GenAI development, agent orchestration, or AI assisted tooling. - Solid software engineering background (Python preferred; experience with APIs and microservices). - Familiarity with structured and semi structured data formats (JSON, PDFs, engineering documentation, etc.). Know how - Good understanding of LLM integration patterns, embeddings, vector stores and RAG architectures - Knowledge of agent frameworks (e.g., LangChain, LlamaIndex, OpenAI Agents, CrewAI, Sw