Description

You will define and drive the AI/ML architecture and roadmap, spanning traditional ML and Generative AI (GenAI) use cases.

Responsibilities

  • Design end-to-end AI solutions covering data ingestion, feature engineering, model training, inference pipelines, and monitoring.
  • Lead the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks using tools like LangChain or LangGraph.
  • Translate business requirements into scalable AI-driven technical solutions by collaborating with stakeholders.
  • Ensure models meet governance, security, explainability, and regulatory compliance while embedding ethical AI principles.
  • Partner with DevOps to establish CI/CD pipelines for AI, covering model versioning and deployment automation.

Required Skills

  • 10+ years of experience leading AI/ML architecture and strategy in enterprise settings.
  • Strong expertise in deploying large-scale AI/ML solutions, including LLMs and RAG frameworks.
  • Proficiency with AI/ML tools and frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, or LangGraph.
  • Deep knowledge of data workflows, feature engineering, model training, evaluation, and deployment.
  • Experience with cloud platforms including AWS, Azure, and GCP for AI deployment.
  • Familiarity with model governance, security, explainability, and ethical AI standards.
  • Experience developing CI/CD pipelines for AI/ML, including model versioning and monitoring.
  • Strong stakeholder management and problem-solving capabilities.

Education

Bachelor's or Master's degrees