Role & responsibilities

Core AI & ML Skills
Hands-on experience building GenAI solutions (LLMs, RAG pipelines, embeddings, semantic search)
Practical use of OCR and document intelligence techniques across unstructured data (PDFs, images, scanned forms)
Robust understanding of NLP concepts (entity extraction, classification, keyword detection)
Experience with agentic / multiagent architectures and workflow-based AI systems
Ability to adapt or fine-tune models for accuracy, confidence scoring, and explainability

Architecture & System Design
Proven ability to design end-to-end AI platforms, beyond proof-of-concepts
Experience with large-scale document pipelines (ingestion processing indexing retrieval)
Robust knowledge of RAG vs alternative architectures (hybrid search,



knowledge graphs, semantic indexing)
Experience with event-driven and serverless patterns for scalable processing
Ability to reason about trade-offs (accuracy vs cost, latency vs scale, complexity vs maintainability)

Cloud & Platform Engineering
Robust experience in at least one major cloud platform (AWS preferred)
Familiarity with:
Object storage (e.g. S3)
Serverless compute (e.g. Lambda)
Managed AI/ML and OCR services
Infrastructure-as-Code mindset (e.g. Terraform or equivalent)
Ability to design cloud-agnostic solutions where required.

📌 Gen Ai +aws Engineer Bengaluru
🏢 Tata Consultancy Services
📍 Bengaluru