AI Engineer

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.

Experience Summary

• 4–8 years of experience as an AI Engineer focused on building and operating LLM-powered solutions for legal, regulatory, and compliance document workflows (e.g., EU AI Act, DSA, Data Privacy, ESG, Security, Compliance).

  
  

• Strong emphasis on reference identification, citation grounding, retrieval quality, traceability, explainability, and evaluation in document-centric AI systems.

  
  

Core Responsibilities / Focus

• Design and implement GenAI and Agentic AI applications for complex document understanding, reasoning, and decision support

  
  

• Build and optimize RAG (Retrieval-Augmented Generation) pipelines tailored to regulatory and legal documents with high precision and grounded responses

  
  

• Develop robust document ingestion and retrieval strategies including contextual chunking, embeddings, metadata enrichment, and semantic indexing

  
  

• Implement reference identification, citation tracking, and traceability mechanisms for document-centric AI workflows

  
  

• Optimize retrieval ranking, semantic search, and grounding to improve answer accuracy and reduce hallucinations

  
  

• Integrate Knowledge Graphs (RDF/SPARQL) with LLM workflows for structured and unstructured reasoning

  
  

• Orchestrate multi-step AI workflows using LangChain, LangGraph, or similar agent frameworks

  
  

• Establish AI quality assurance and evaluation practices including retrieval evaluation, hallucination detection, LLM judge frameworks, and RAGAS-style scoring

  
  

• Build, train, and fine-tune specialized NER and document understanding models

  
  

• Ensure explainability, auditability, and compliance of AI outputs in regulated environments

  
  

• Support end-to-end model lifecycle activities including experimentation, versioning, deployment readiness, and monitoring handover

  
  

Core Skills (Must-Have)

• Python (primary)

  
  

• Docker / Docker Compose

  
  

• NLP / NLU

  
  

• GenAI / LLM application development

  
  

• Agentic AI

  
  

• RAG (Retrieval-Augmented Generation)

  
  

• Embeddings

  
  

• Contextual chunking strategies

  
  

• Knowledge Graphs (RDF)

  
  

• SPARQL

  
  

• Model lifecycle / ML application lifecycle

  
  

• LangChain

  
  

• LangGraph

  
  

• Git

  
  

• AI QA / evaluation (e.g., RAGAS, LLM judges, retrieval and answer quality validation)

  
  

Nice-to-Have

• Java

  
  

• Kubernetes

  
  

• Dev Containers

  
  

• GitOps

  
  

• Documentation practices

  
  

• Deepagents (or similar advanced agent frameworks)

  
  

Domain Advantage

• Experience with legal, regulatory, compliance, and policy documents

  
  

• Understanding of requirements around auditability, explainability, and risk controls in AI systems

  
  

Educational qualification:

BE/B.Tech or Equivalent Degree

Experience :

4-8 Years

Mandatory/requires Skills :
Strong hands-on expertise in Python (or Java), NLP, RegEx, SpaCy, NLTK, and transformer-based models.

Preferred Skills :