RAG Architect(GenAI Architect)

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 28,200+ 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 :

Education and Work Experience Requirements:  
·       5 to 8 years of experience as Data Science Architect
·       2 to 3 years of experience in Generative AI solution development
·       Proven track record and experience with with GenAI technologies
o Open source LLMs like Llama, Gemma, Mixtral etc
o Closed source LLMs such as Open AI GPT, Azure Open AI, Claude, Gemini etc
o Prompt Engineering/Tuning, RAG, RAFT, LLM finetuning such as PEFT(LoRA, QLoRA ..)
o Understanding of SLMs such as Phi3,QWEN, BERT and Transformer architecture
o Vector databases like Pinecone, Qdrant etc.
·       Good knowledge of advanced statistical methods. Experience working with Text Data using transformer-based model
·       Expertise with the following scripting languages:
o Python, R, Tensorflow, Keras, Pytorch
o OpenNLP, CoreNLP, WordNet, NLTK, SpaCy, Gensim, Large Language Models, Knowledge Graphs
·       Design and implement end-to-end Generative AI solutions, ensuring seamless integration with enterprise applications and workflows.
·       Lead technical evaluations and POCs (Proof of Concepts) to assess new AI models, frameworks, and vector databases for RAG solutions.
·       Develop scalable indexing and retrieval strategies to optimize search and generation performance in large-scale AI systems.
·       Implement hybrid search techniques, including dense and sparse retrieval, for enhanced information retrieval accuracy.
·       Define and enforce architectural standards, coding best practices, and performance benchmarks for RAG-based applications.
·       Collaborate with business leaders to identify AI-driven opportunities and develop strategic roadmaps for AI product evolution.
·       Drive the adoption of domain-specific AI solutions by tailoring RAG architectures to industry-specific requirements.
·       Establish feedback loops and model monitoring mechanisms to ensure continuous improvement of AI-generated outputs.
·       Utilize MLOps best practices to automate model deployment, monitoring, and retraining pipelines for Generative AI solutions.
·       Optimize knowledge graphs and vector embeddings to enhance contextual awareness in Graph RAG implementations.
·       Develop strategies for handling long-context retrieval and efficient chunking mechanisms for better AI response quality.
·       Leverage fine-tuning and reinforcement learning with human feedback (RLHF) to improve generative AI model performance.
·       Explore and integrate federated learning techniques to enable privacy-preserving AI model training and inference.
·       Conduct AI ethics assessments and bias mitigation strategies to ensure responsible AI development and deployment.
·       Engage with open-source AI communities and contribute to research publications or technical blogs on RAG advancements.
·       Participate in technical panels, conferences, and industry events to showcase AI expertise and thought leadership.
·       Support sales and pre-sales teams by providing technical guidance, solution demonstrations, and AI-driven business value assessments.
·       Establish AI Centers of Excellence (CoE) within the organization to drive innovation, knowledge sharing, and AI capability building.
·       Ensure compliance with enterprise security policies, data governance regulations, and responsible AI guidelines.
·       Develop multi-modal AI capabilities that integrate NLP, Computer Vision, and Speech Recognition for advanced generative applications.
·       Prior experience working on Mobility, Manufacturing or Healthcare domain will be a plus.
 
 Mandatory Skills:  
·       Design, develop, test, and deploy Machine Learning models using state-of-the-art algorithms with a strong focus on language models.
·       Strong understanding of LLMs, and asso


 

Qualifications

Educational qualification:

BE/BTech or MCA 

Experience : 10-15 years

Mandatory/requires Skills : AI

Preferred Skills :