AI Platform Engineer

Description

The company runs and modernizes mission-critical technology systems for large businesses, using proven expertise and AI-driven insight.

The role sits in a large platform modernization effort that is strengthening AI and machine learning capabilities on Microsoft Azure.

You would help design, build and run a central AI platform, bringing enterprise-grade AI into the platform engineering setup to automate work, improve data security and speed up business results.

Responsibilities

• Design and assess serverless compute architectures for complex AI workloads.
• Implement and manage scalable Azure Databricks Serverless environments built around enterprise data needs.
• Build, automate and maintain CI/CD pipelines in Azure DevOps for AI and Databricks workloads.
• Keep Databricks and serverless services reliable, observable, monitored and optimized.
• Work as an independent expert alongside Data Science, Cloud Engineering and DevOps teams.
• Advise on best practices and technical alignment for putting AI models into production efficiently.
• You will also lead supporting capabilities such as AI SDK development, data masking, PII detection and document intelligence, integrating Azure AI services with modern DevOps practices while meeting enterprise governance standards for performance, reliability and compliance.

Requirements

• Show a proven record of designing and deploying AI and ML solutions on Azure, with deep knowledge of Azure Databricks Serverless architectures.
• Have hands-on experience with serverless tools such as Azure Functions, Event Grid and Logic Apps.
• Program strongly in Python, PySpark and SQL for data engineering and model integration.
• Bring expertise in CI/CD, MLOps and Infrastructure-as-Code using Azure DevOps and Terraform.
• Understand cloud cost management, scaling, observability, monitoring and alerting for cloud environments.
• Know enterprise security, data protection and compliance requirements for AI workloads.
• Have a proven record of integrating large language models, such as Mistral AI, into corporate or fintech environments.
• Be a growth-minded, customer-focused person who drives your own development and works inclusively with others.
• Optional: Advanced Microsoft certifications, such as Azure AI Engineer Associate or Azure Data Engineer Associate.
• Optional: Practical experience building AI SDKs and using Document Intelligence or similar AI data extraction tools.
• Optional: Background working in fintech or other highly regulated, complex enterprise environments.
• Optional: Strong grasp of responsible AI adoption practices at enterprise scale.

Conditions

Hybrid-friendly work culture.

Equal-opportunity statement: the company welcomes people of all backgrounds and encourages applications even if you do not meet every requirement.

Benefits

• Be Well programs covering financial, mental, physical and social health.
• Certifications with Microsoft, Google and Amazon, along with coaching and hands-on learning.
• Personalized development goals, career-path tools and continuous feedback.
• Possible career paths horizontally into other technical or non-technical areas, or vertically into senior leadership or specialist roles such as Cloud Architecture or Principal AI Engineering.