AI Expertise Development Lead

5 days ago

Chennai, Tamil Nadu, India beBeeArtificialintelligence Full time ₹ 2,30,00,000 - ₹ 3,05,00,000
Job Description:

We are seeking a seasoned AI expert to lead our cutting-edge AI initiatives and drive innovation in firmware and data center AI solutions. This role requires a strategic thinker who can design, deploy, and integrate large-scale AI architectures, leveraging retrieval-augmented generation (RAG) and agentic AI to deliver scalable and high-performance solutions.

The ideal candidate will have a deep understanding of LLMs, code generation, and RAG, as well as experience in developing intelligent autonomous agents that interact with data, APIs, and workflows. They will be responsible for leading the design and deployment of AI-driven solutions, focusing on code synthesis, automated testing, and software development workflows.

Required Skills and Qualifications:
  • Education: Computer Science or a related field
  • Experience: 5+ years in AI and machine learning, with at least 2 years of experience working on LLMs, code generation, RAG, or AI-powered automation
  • Technical skills:
    • Proficiency in Python, TensorFlow, PyTorch, and LangChain
    • Experience with LLM fine-tuning for code generation
    • Strong expertise in vector databases (FAISS, Weaviate, Chroma, Pinecone, Milvus) and retrieval models
    • Hands-on experience with AI-powered code assistants (Copilot, Code Llama, Codex, GTP-4)
    • Knowledge of automated software testing, AI-driven test case generation, and AI-assisted debugging
    • Experience with multi-agent AI systems for autonomous coding tasks
Benefits:

This is an exciting opportunity to join our team and contribute to the development of cutting-edge AI solutions. As a Principal AI Engineer, you will have the chance to work on high-profile projects, collaborate with experienced professionals, and develop your skills in AI and machine learning.

Others:

As a successful candidate, you will have the opportunity to:

  • Develop novel approaches to solve complex problems in firmware lifecycle management and customer support
  • Implement advanced natural language processing and computer vision models to extract insights from diverse data sources
  • Automate model lifecycle management and stay updated with AI and machine learning technology advancements

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