Description

Define and drive the AI/ML architecture and roadmap for traditional machine learning and Generative AI use cases.

You will own the release pipeline and model governance for scalable enterprise AI solutions.

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 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.

Preferred Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Key Skills

Education

Bachelor's or Master's degrees