Innovation Platform Engineer

Overview

In this role, you will build and evolve cloud-based innovation platforms to support AI, automation and digital transformation for a leading international law firm. You’ll work across Azure and GCP with cross-functional teams to turn ideas into secure, scalable production services. You’ll prototype, implement, and govern platform solutions while advancing security and operational standards. This is a hands-on engineering position with a strong emphasis on experimentation and impactful AI delivery.

Responsibilities

• Build and evolve innovation platforms across Microsoft Azure and Google Cloud Platform
• Develop reusable cloud architectures, landing zones, deployment pipelines and shared engineering services
• Automate cloud environments using infrastructure as code and DevSecOps practices
• Build prototypes and proof-of-concept solutions, preparing successful projects for production
• Engineer AI solutions using Azure AI, Vertex AI, large language models and emerging agentic frameworks
• Establish monitoring, operational standards, security controls and platform governance
• Develop, implement, and manage the innovation platform to support legal services
• Collaborate with IT specialists to integrate new technologies into existing systems
• Ensure continuous enhancement and upgradation of the innovation platform as per the industry standards
• Diagnose and resolve issues related to the platform infrastructure
• Assist in training team members and stakeholders on new technology implementations

Key requirements

• Strong hands-on engineering experience across Azure and GCP
• Experience building cloud-native platforms, infrastructure as code and automation
• CI/CD pipeline development and DevSecOps experience
• Knowledge of Docker, Kubernetes and secure, API-driven architectures
• Practical experience developing AI solutions using LLMs and AI engineering platforms
• Familiarity with GitHub, Azure DevOps and automated deployment tools
• Exposure to Power Platform or other low-code/no-code tools would be useful

• Practical approach to experimentation
• Strong technical problem-solving skills
• Clear沟munication with technical and business stakeholders
• Azure and Google Cloud Platform (GCP)
• Cloud-native platform development
• Infrastructure as code (IaC) and automation

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