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As an AI Platform Engineer within the domain, you will play a key role in building and evolving the bank’s central AI platform. This platform underpins AI and data science initiatives across the organization, enabling teams to develop, deploy, and scale machine learning solutions in a secure, compliant, and efficient manner. You will work closely with AI engineers, data scientists, and platform teams to deliver robust, reusable capabilities that accelerate AI adoption across the bank. The focus is on creating scalable platform services, improving developer experience, and ensuring production-grade AI solutions.
Job Responsibility:
Design, build, and enhance central AI platform capabilities used by multiple AI teams
Develop and maintain reusable platform services for model development, deployment, and monitoring
Enable and support AI teams in engineering best practices, tooling, and platform usage
Collaborate with data scientists and ML engineers to productionize machine learning models
Improve platform reliability, scalability, and performance within a cloud-based ecosystem
Contribute to automation, CI/CD pipelines, and MLOps practices
Ensure compliance with security, risk, and regulatory standards within the banking environment
Requirements:
Strong programming skills in Python
Hands-on experience with Databricks (workflows, notebooks, clusters)
Proven experience in AI/ML engineering or platform engineering environments
Experience with MLOps practices (CI/CD, model deployment, monitoring)
Familiarity with cloud platforms (e.g., Azure, AWS, or GCP)
Experience working in complex, regulated environments is a plus
Nice to have:
Experience building internal developer platforms or shared services
Knowledge of containerization (Docker, Kubernetes)
Understanding of data engineering concepts (ETL pipelines, data workflows)
Exposure to model lifecycle management and governance