Description

Define and drive the AI/ML architecture and roadmap for enterprise-scale Generative AI and traditional ML solutions.

This role is hybrid.

Responsibilities

• Design end-to-end AI solutions covering data ingestion, feature engineering, model training, inference, and monitoring.
• Lead the integration of LLMs and RAG frameworks using tools like LangChain or LangGraph.
• Partner with DevOps to establish CI/CD pipelines for AI, handling model versioning and A/B testing.
• Ensure models meet governance, security, explainability, and ethical AI compliance standards.

Required Skills

• 10+ years of experience leading AI/ML architecture and strategy in enterprise environments.
• Hands-on experience with TensorFlow, PyTorch, Hugging Face, LangChain, and LangGraph.
• Deep understanding of data workflows, feature engineering, and scalable deployment strategies.
• Experience building agentic AI solutions, including tracing frameworks and LLM observability.
• Knowledge of cloud platforms (AWS, Azure, GCP) for AI deployment.
• Experience developing CI/CD pipelines for AI/ML, including monitoring and performance tuning.
• Familiarity with model governance, security, and ethical AI standards.

Preferred Skills

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

Key Skills

Education

Bachelor's or Master's degrees