Technology

Principal Engineer - AI & ML

Mumbai
Work Type: Full Time

Seeking a highly experienced Senior AI/ML Architect with over 12 years of professional experience to lead the design and development of our next-generation conversational AI platforms

 The ideal candidate will be a visionary in the field, possessing deep expertise in Text-to-SQL technologies and a proven track record of architecting scalable, enterprise-grade chatbot solutions.

Core Responsibilities

  • Architectural Leadership: Design end-to-end conversational AI architectures, integrating LLMs with enterprise data sources using Text-to-SQL and RAG (Retrieval-Augmented Generation) frameworks.
  • Text-to-SQL Development: Build and optimize high-accuracy Natural Language to SQL engines that enable non-technical users to query complex relational databases through chat interfaces.
  • System Integration: Connect AI models (OpenAI, Hugging Face) with internal databases, APIs, and cloud services (AWS, Azure, or GCP) ensuring scalability and security.
  • Performance Optimization: Oversee the fine-tuning of Large Language Models (LLMs) and the optimization of prompt engineering strategies to improve system accuracy and response latency.
  • Cross-Functional Collaboration: Partner with business leaders and engineering teams to translate complex AI concepts into actionable product features and business insights.

Required Qualifications & Skills

  • Experience: Minimum 12+ years of total experience in software engineering, with at least 5-6 years focused on AI/ML and Natural Language Processing (NLP).
  • Technical Expertise:
    • Expert-level proficiency in Python and advanced SQL.
    • Deep understanding of Generative AI, Transformers, and LLM orchestration tools like LangChain or LlamaIndex.
    • Proven experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Database & Data Engineering: Strong background in relational databases (PostgreSQL, SQL Server) and NoSQL/Graph databases for managing large-scale data streams.
  • Cloud Platforms: Hands-on experience with cloud AI services like AWS SageMaker or Google Cloud AI.
  • Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related field.


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