Chief Generative AI Architect

2 days ago

Nagpur, Maharashtra, India beBeeMachineLearning Full time ₹ 30,00,000 - ₹ 50,00,000
Senior Machine Learning Engineer

We are seeking a seasoned engineer with deep expertise in machine learning and generative AI systems. This role is ideal for someone who can drive technical direction, ensure AI products deliver measurable business value from day one, and lead the engineering team.

Key Responsibilities
  • Build Next-Gen LLM Solutions
    • Design, fine-tune, and deploy large language model–based systems using advanced techniques such as prompt engineering, retrieval-augmented generation (RAG), and agent frameworks.
  • Take Ownership of Codebase
    • Deliver production-grade, reusable, and scalable code in Python and SQL, leveraging libraries like LangChain and LangGraph.
  • Cloud Deployment
    • Architect and optimize deployment pipelines on cloud platforms (Azure, AWS, or GCP), ensuring CI/CD, scalability, and cost-efficiency.
  • Collaborate Across Functions
    • Translate complex technical concepts into actionable insights for product owners, data scientists, and domain SMEs.
  • Lead and Mentor
    • Provide technical leadership, coach junior team members, and foster a culture of best practices in machine learning and LLM engineering.
  • Stay Ahead of the Curve
    • Continuously experiment with new research, tools, and methods in generative AI to keep our solutions cutting-edge.

Requirements

  • 5+ years of professional experience in developing and deploying ML models in production environments.
  • At least 1 year of practical experience working with large language models and generative AI, including prompt design, RAG pipelines, and AI agents.
  • Proven ability to set and guide a technical roadmap for engineering teams.
  • Advanced programming proficiency in Python and SQL with strong expertise in LangChain/LangGraph.
  • Familiarity with cloud ecosystems (Azure, AWS, or GCP) and modern DevOps practices.
  • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.

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