AI Engineer
Bosch•4h ago
bengaluru, inOnsiteFull-timeMid Level4+ yrs exp
Top focus
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
- 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
- evaluation in document-centric AI systems. Core Responsibilities / Focus Design and implement GenAI and Agentic AI applications for complex document understanding, reasoning
- 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
- semantic indexing Implement reference identification, citation tracking
- traceability mechanisms for document-centric AI workflows Optimize retrieval ranking, semantic search
- 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
- similar agent frameworks Establish AI quality assurance and evaluation practices including retrieval evaluation, hallucination detection, LLM judge frameworks
- RAGAS-style scoring Build, train
- fine-tune specialized NER and document understanding models Ensure explainability, auditability
- compliance of AI outputs in regulated environments Support end-to-end model lifecycle activities including experimentation, versioning, deployment readiness
- 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
- policy documents Understanding of requirements around auditability, explainability
- 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
- transformer-based models . Preferred Skills :
Required skills
PythonDockerNLPNLUGenAILLMAgentic AIRAGEmbeddingsKnowledge GraphsSPARQLLangChainLangGraphGit