Our client needs someone who can pick up existing solutions already in production, work through an active change-request backlog, and extend them — with room to build new capability where it fits.The client runs a live pipeline of finance data/AI solutions — end-to-end builds spanning data pipelines, data models, and the applications on top, plus machine learning components handling specific pieces of the workload (e.g. forecasting, anomaly detection).

Responsibilities

• Maintain and further develop existing finance data/AI solutions, and develop new ones
• Build and operate finance data pipelines, ML/GenAI solutions, agents and applications on Databricks and Azure
• Perform Data/ML/AI Ops: CI/CD pipelines (e.g. Azure DevOps), deployment, monitoring, retraining, model evaluation
• Work AI-enabled: use GitHub Copilot, Genie Code and similar tools to accelerate delivery
• Reuse patterns and build reusable data products

Required Experience

• Data engineering, AI engineering, machine learning and application development — Python, SQL, ML/GenAI frameworks, agent/LLM tooling
• Databricks and Azure hands-on
• Data/ML/AI Ops and CI/CD with Azure DevOps or equivalent
• Strong AI-enabled development using GitHub Copilot, Genie Code and similar tools

Nice to Have

• Prior experience working in Finance context.

This is a hands-on-from-day-one role — there's an active change-request backlog waiting, and the client wants someone who can get productive fast.