Chief AI Architect

2 days ago

Kollam, Kerala, India beBeeInnovator Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Lead AI Innovator

Our organization is seeking a seasoned AI professional to spearhead the development and deployment of cutting-edge, agent-based workflows that redefine personalized insights.

You will focus on implementing retrieval-augmented generation (RAG) pipelines for semantic search, personalization, and contextual enrichment.

This role is ideal for an individual with a strong passion for applied AI and engineering who can design, optimize, and deploy AI systems that go beyond prototypes and into real-world, production-grade systems.

Key ResponsibilitiesAI & Agentic Workflows
  • Develop RAG pipelines for semantic search, personalization, and contextual enrichment.
  • Implement agentic AI workflows using Pinecone, LangChain/LangGraph, and custom orchestration.
  • Integrate large language model (LLM)-driven features into production systems, balancing innovation with scalability.
Vector Search & Data Intelligence
  • Design and optimize vector databases (Pinecone, FAISS, Milvus) for low-latency retrieval.
  • Work with structured/unstructured datasets for embedding, indexing, and enrichment.
  • Collaborate with data engineers on extract, transform, load (ETL)/extract, load, transform (ELT) pipelines to prepare data for AI applications.
Collaboration & Agile Delivery
  • Partner with backend and frontend engineers to integrate AI features into user-facing products.
  • Participate in agile ceremonies (sprint planning, reviews, standups).
  • Maintain clear documentation and support knowledge sharing across the AI team.
Technical Requirements
  • AI Tools: Pinecone, LangChain, LangGraph, OpenAI APIs (ChatGPT, GPT-4/5), HuggingFace models
  • Languages: Python (primary for AI workflows), basic Node.js knowledge for integration
  • Cloud & DevOps: AWS (Lambda, S3, RDS, DynamoDB, IAM), Docker, continuous integration/continuous deployment (CI/CD) pipelines
  • Data Engineering: SQL, Python (Pandas, NumPy), ETL/ELT workflows, databases (Postgres, DynamoDB, Redis)
  • Bonus Exposure: React, Next.js

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