AI Engineer

About Blu Parrot

Blu Parrot Ventures is an innovative, award-winning AI company (recognized as 'AI Company of the Year 2025' at the India CISO Summit & Awards) specializing in Data Science, Artificial Intelligence, Generative AI solutions, digital transformation, and cutting-edge products like Talkie AI (an intelligent voice agent platform). We're a fast-growing, bootstrapped enterprise tech firm delivering impactful AI solutions globally, with a strong focus on offline-capable and production-grade AI deployments. Join us to build next-gen AI products in a dynamic, high-ownership environment!

About the Role

We're hiring an AI Engineer for a full-time, on-site position at our Sector 44 office in Gurugram. This long-term role focuses on developing one of our most innovative AI-driven products using Large Language Models (LLMs) and advanced Generative AI. Ideal for someone with 1.5–2 years of solid experience who has a strong "Can-Do" attitude and loves tackling complex, real-world AI challenges.

Key Responsibilities

• Develop and deploy high-performance AI/LLM solutions, with emphasis on offline/edge deployments.
• Build and optimize offline AI applications and ensure reliable offline LLM inference.
• Design scalable LLM architectures, implement token-by-token generation, and maintain zero token loss in processing.
• Optimize RAG pipelines using Hybrid RAG, Graph-based RAG, advanced chunking, query rewriting, retrieval tuning, and LLM fine-tuning.
• Reduce hallucinations, enhance factual accuracy, and implement robust mitigation strategies for production reliability.
• Collaborate on integrating AI features into live products and contribute to end-to-end innovation.

Must-Have Requirements

• 1.5 to 2 years of hands-on experience in AI/ML engineering (strictly required – we need proven production-level exposure).
• Strong expertise in Natural Language Processing (NLP) and Generative AI.
• Practical experience with offline deployment of LLMs and building offline AI applications (non-negotiable).
• Deep familiarity with:
  • Designing/scaling LLM architectures.
  • Token-by-token implementation and zero-loss processing.
  • Advanced RAG optimization (Hybrid/Graph RAG, chunking strategies, query rewrite, retrieval enhancement, fine-tuning).
  • Hallucination reduction and accuracy improvement techniques.
• Proficiency in Python, Hugging Face Transformers, PyTorch, LangChain/LlamaIndex, and model optimization/quantization tools.
• Ability to deliver clean, production-ready code independently.

Preferred (Nice-to-Have)

• Experience with edge inference (ONNX, TensorRT, local serving).
• Exposure to voice AI, multi-modal models, or agentic systems.
• Prior work in startups or fast-paced AI product teams.