AI Engineer/ Gen AI

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

RoleAgile Architect

Qualifications

BACHELOR OF COMPUTER APPLICATION, BACHELOR OF COMPUTER SCIENCE, BACHELOR OF TECHNOLOGY