Chief AI Architect

7 days ago

Hyderabad, Telangana, India beBeeSenior Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Opportunity

Uplevyl is seeking a visionary Senior AI Engineer to lead the design and deployment of cutting-edge AI-powered workflows that revolutionize personalized insights.

This opportunity allows someone passionate about applied AI and engineering to build, optimize, and deploy production-grade AI systems that go beyond prototypes.

Key Responsibilities:

AI & Agentic Workflows

  • Design and implement retrieval-augmented generation pipelines for semantic search, personalization, and contextual enrichment.
  • Build agentic AI workflows using Pinecone, LangChain/LangGraph, and custom orchestration.
  • Integrate large language model-driven features into production systems, balancing innovation with scalability.

Vector Search & Data Intelligence

  • 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 extract-transform-load/load 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.

Tech Stack

  • 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, 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 (Pinecone, FAISS, Milvus), and LLM integration
  • Strong background in Python for AI workflows (embeddings, orchestration, optimization)
  • Familiarity with agentic architectures (LangChain, LangGraph, or similar)
  • Experience deploying and scaling AI features on AWS 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 (GDPR, HIPAA, SOC 2)
  • Exposure to personalization engines, recommender systems, or conversational AI

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