Chief Artificial Intelligence Developer

2 weeks ago

Varanasi, Uttar Pradesh, India beBeeEngineering Full time US$ 1,50,000 - US$ 2,00,000

Lead AI Architect

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About this Opportunity:

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  • Join a team that is shaping the future of personalized insights.
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Key Responsibilities:

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  • 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 LLM-driven features into production systems, balancing innovation with scalability.">
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Vector Search & Data Intelligence:

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  • 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.">
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Collaboration & Agile Delivery:

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  • 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.">
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Tech Stack:

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  • 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">
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Required Qualifications:

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  • 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.">
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Preferred Skills:

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  • 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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