Description

You will define and drive the AI/ML architecture and roadmap, focusing on both traditional ML and Generative AI use cases.

Responsibilities

• Design end-to-end AI solutions covering data ingestion, feature engineering, model training, inference, and monitoring.
• Lead 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 ethical AI standards throughout the design process.
• 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 designing and 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 understanding of data workflows, feature engineering, model training, and deployment.
• Knowledge of 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 monitoring and tuning.
• Strong problem-solving and stakeholder management skills.

Key Skills

Education

Master's degree