[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Tata Consultancy Services jobs](https://jobs.opennash.com/companies/tata-consultancy-services/) · [Search jobs](/search/) Tata Consultancy Services · Bengaluru # AI Engineer/ Gen AI Bengaluru Operations Last seen on Tata Consultancy Services’s official careers site on August 1, 2026; it may have closed since. [Apply on Tata Consultancy Services’s careers site →](https://ibegin.tcsapps.com/candidate/next/en-IN/jobs/425313J) [OpenNash Jobs](https://jobs.opennash.com/) / [Tata Consultancy Services](https://jobs.opennash.com/companies/tata-consultancy-services/) / AI Engineer/ Gen AI ## Job description Required 5-10years Hands-on Architect to design and scale enterprise insight platforms powered by modern data, AI, and Generative AI ecosystems. This role focuses on enabling self-service analytics and intelligent decision-making using platforms such as Dataiku (on EKS), Posit, and AWS SageMaker, while embedding GenAI-driven insight capabilities across the data lifecycle. You will bridge data engineering, data science, and business domains to deliver scalable, governed, and AI-powered insight solutions. ### Desired skill - Strong experience in data/AI architecture, insight enablement, or analytics platforms Hands-on expertise with: Dataiku (including EKS deployment) Posit (RStudio/Workbench) AWS SageMaker (training, deployment, pipelines) - Strong understanding of: Modern data architectures (Datamesh, lakehouse, semantic layers, data products) GenAI patterns (RAG, agents, prompt engineering) MLOps/DataOps practices - Proficiency in Python and/or R ### Key Responsibilities Platform & Architecture Architect and design AI &ML ecosystems leveraging Dataiku (on Kubernetes / EKS), Posit, and SageMaker. Define cloud-native architectures on AWS integrating EKS, S3, Lambda, API Gateway, and SageMaker for analytics and AI workloads. GenAI Enablement & Patterns Self-Service & Insight Delivery Governance, MLOps & Observability Collaboration & Enablement Tools, Libraries & Frameworks Enable and standardize usage of: LangChain, LangGraph, LlamaIndex for orchestration and agent design Hugging Face Transformers for model integration and experimentation Vector databases (FAISS, OpenSearch, Pinecone, Chroma) ML/AI frameworks (PyTorch, TensorFlow, scikit-learn) ### Integrate GenAI workflows into Dataiku pipelines (recipes, plugins, scenarios) Posit notebooks and analytical workflows SageMaker pipelines and endpoints