Description

Define and drive the AI/ML architecture and roadmap, including traditional machine learning and Generative AI use cases. 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) using LangChain, LangGraph, or similar tools. Collaborate with stakeholders to translate requirements into scalable technical solutions. Ensure models adhere to governance, security, and regulatory compliance standards.

Responsibilities

• Design and deploy large-scale AI/ML solutions, including LLMs and RAG frameworks.
• Develop agentic AI solutions with tracing frameworks and LLM observability.
• Establish CI/CD pipelines for AI, including model versioning and A/B testing.
• Guide engineering teams in implementing scalable and reliable AI components.
• Evaluate and select appropriate AI tools, cloud services, and frameworks.

Required Skills

• 10+ years of experience leading AI/ML architecture in enterprise environments.
• Deep expertise in LLMs, RAG, and Agentic AI design.
• Hands-on experience with TensorFlow, PyTorch, and Hugging Face.
• Proficiency with LangChain, LangGraph, or similar frameworks.
• Strong knowledge of AWS, Azure, and GCP for AI deployment.
• Experience with CI/CD, model observability, and performance tuning.
• Understanding of data workflows, feature engineering, and model governance.

Preferred Skills

• Advanced degree (Ph.D., Master’s) in Computer Science, Data Science, or related fields.
• Publications or contributions to AI research and open-source projects.

Key Skills

Education

Bachelor's degree