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.