Description

You will define and drive the AI/ML architecture and roadmap for investment banking solutions, leveraging Generative AI and Azure OpenAI.

This role is on-site.

Responsibilities

• Design end-to-end AI solutions covering data ingestion, feature engineering, model training, inference pipelines, and monitoring.
• Lead the integration of LLMs and RAG frameworks using LangChain, LangGraph, or similar tools.
• Collaborate with stakeholders to translate business requirements into scalable, secure, and compliant AI-driven technical solutions.
• Guide engineering teams in implementing AI components with a focus on scalability, reliability, and performance optimization.
• Partner with DevOps to establish CI/CD pipelines for AI, including model versioning, deployment automation, and A/B testing.

Required Skills

• 10+ years of experience leading AI/ML architecture and strategy in enterprise environments.
• Strong expertise in designing and deploying large-scale AI/ML solutions, including LLMs and RAG.
• Hands-on experience with TensorFlow, PyTorch, Hugging Face, LangChain, and LangGraph.
• Deep understanding of data workflows, feature engineering, model training, evaluation, and deployment.
• Knowledge of cloud platforms (AWS, Azure, GCP) and services tailored for AI deployment.
• Familiarity with model governance, security, explainability, and ethical AI standards.
• Experience developing CI/CD pipelines for AI/ML, including model versioning, monitoring, and performance tuning.

Preferred Skills

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

Key Skills

Education

Any Graduate