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:

• Implementation & validation of AI-powered solutions with modular, reusable components using Python, REST APIs & in-house developed AI framework/s.

• Contribute to the development of AI pipelines, from data ingestion to model deployment and monitoring.

• Collaborate across domains to integrate AI/LLM capabilities to realize use cases such as AI-powered ASPICE assessments, Artefacts evaluation, etc.

•  Optimize agent behavior for safety, efficiency, and explainability.

Technical Skills:

• Strong programming background in Python with experience in AI/ML frameworks (e.g., LangChain, Hugging Face, OpenAI APIs).

• Knowhow of RAG concept.

• Understanding of LLMs, Embeddings, and multi-model reasoning.

• API orchestration, and GenAI prompt engineering.

• Familiarity with tools like Git,GITHUB ,versioning concepts.

• Strong analytical and problem-solving skills with a user-centric design mindset.

• Familiarity of A2A,MCP protocols.+

• Workflow Management: Experience with workflow automation tools like PowerAutomate, n8n,

• Hands-on experience with GenAI foundation models and vector databases, leveraging foundational AI models for advanced capabilities.

• Familiarity with automotive standards such as ASPICE PAM model .(Good to have)

Educational qualification:

• Any Bachelor’s or Master’s degree

• 3–4 years of hands-on experience in AI model development, deployment, and optimization.

• Strong command of Python and libraries

• Deep understanding of machine learning algorithms, model training workflows, and deep learning architectures (CNN, RNN, Transformers).

• Experience with data wrangling, preprocessing, and feature engineering for model readiness.

• Skilled in developing and integrating models via APIs (Flask, FastAPI) and containerization using Docker.

• Proficiency in model evaluation metrics, hyperparameter tuning, and performance analysis.

• Experience with Git and collaborative code development workflows.

• Strong analytical mindset and ability to troubleshoot complex model behaviors.

Preferred Qualifications:

• Experience working with Large Language Models (LLMs), Generative AI, or prompt engineering

• Familiarity with cloud AI platforms

• Knowledge of MLOps practices — CI/CD for ML, model monitoring, and retraining pipelines.

• Exposure to computer vision or NLP-based AI systems.

• 3–4 years of hands-on experience in AI model development, deployment, and optimization.