Lead AI Engineer for Personalized Insights

1 week ago

Mysore, Karnataka, India beBeeEngineer Full time ₹ 18,00,000 - ₹ 22,50,000
About the Position

Our organization seeks an experienced engineer to lead AI-powered initiatives that shape personalized insights.

This role focuses on developing and deploying workflows for vector search, retrieval-augmented generation (RAG), and intelligent automation.

The ideal candidate will collaborate with cross-functional teams to bring scalable GenAI features into production.

Key ResponsibilitiesAI & Workflow Development
  • Design and implement RAG pipelines for semantic search, personalization, and contextual enrichment.
  • Build agentic AI workflows using Pinecone, LangChain/LangGraph, and custom orchestration.
  • Integrate LLM-driven features into production systems.
Vector Search & Data Analysis
  • Architect 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 ETL/ELT pipelines to prepare data for AI applications.
Team 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 team.
Tech Stack
  • AI Tools: Pinecone, LangChain, LangGraph, OpenAI APIs (ChatGPT, GPT-4/5), HuggingFace models
  • Languages: Python (primary for AI workflows), Node.js knowledge for integration
  • Cloud & DevOps: AWS (Lambda, S3, RDS, DynamoDB, IAM), Docker, CI/CD pipelines
  • Data Engineering: SQL, Python (Pandas, NumPy), ETL/ELT workflows, Databases (Postgres, DynamoDB, Redis)
  • Bonus Exposure: React, Next.js
Required Qualifications
  • 5+ years in AI/ML engineering or software engineering with applied AI focus.
  • Hands-on experience with RAG pipelines, vector databases, and LLM integration.
  • Strong background in Python for AI workflows.
  • Familiarity with agentic architectures.
  • Experience deploying and scaling AI features on cloud environments.
  • Strong collaboration and communication skills for cross-functional teamwork.
Preferred Skills
  • Experience with embedding models, HuggingFace Transformers, or fine-tuning LLMs.
  • Knowledge of compliance frameworks.
  • Exposure to personalization engines, recommender systems, or conversational AI.

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