AI Engineer/ Gen AI
TCS · Chennai
Source and collection record
Last observed by our collector: . This is not a manual review or a confirmation from the employer.
Employer requisition: 425311
Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.
Your application evidence checklist
Mark the statements you can support after reading the employer source. This checklist stays on this page; it does not score your eligibility or submit an application.
0 of 3 checks marked. Keep unresolved requirements as questions for the employer.
Collected role 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 </div
Collected minimum qualification
BACHELOR OF COMPUTER APPLICATION, BACHELOR OF COMPUTER SCIENCE, BACHELOR OF TECHNOLOGY
Collected experience requirement
5 - 10 Years