AI Cloud Engineer

Overview

Design, build and operate secure, scalable, enterprise-grade cloud platforms that enable advanced AI and Generative AI solutions across the organization.

What you'll do

• Design, develop and deploy cloud-native AI solutions from proof of concept through production deployment.
• Build and manage scalable AI application infrastructure leveraging Azure cloud services, containerized architectures and modern software engineering practices.
• Implement and support Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI and AI-powered automation solutions across enterprise business functions.
• Develop and maintain API-driven integrations with enterprise platforms including Microsoft Graph, SharePoint, Microsoft Fabric, Snowflake, Power BI and other business applications.
• Collaborate with AI engineers, data engineers, architects, cybersecurity teams and business stakeholders to deliver secure and production-ready AI solutions.
• Design and implement CI/CD pipelines, automated deployment frameworks, monitoring solutions and operational best practices for AI workloads.
• Deploy and manage AI applications using Azure Container Apps, cloud-native services and infrastructure automation techniques.
• Ensure compliance with enterprise security, governance, responsible AI and regulatory requirements, particularly within healthcare and other regulated environments.
• Contribute to platform standardization, architecture reviews, technical documentation and cloud engineering best practices.

What you'll need

• Bachelor's Degree or higher in Computer Science, Engineering, Data Science, Mathematics, Information Technology or a related technical field AND 5-7 years of job-related experience, OR High School Diploma/GED AND 10 years of the same job-related experience.
• Proficiency in Python and modern API development frameworks such as FastAPI.
• Hands-on experience with Microsoft Azure and cloud-native application development.
• Strong experience with Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Container Apps, Azure Functions and related Azure platform services.
• Experience building and deploying enterprise-scale AI/ML and Generative AI solutions in cloud environments.
• Working knowledge of Retrieval-Augmented Generation (RAG), vector search architectures, prompt orchestration and Agentic AI systems.
• Experience with Docker containerization and cloud deployment patterns.
• Experience implementing CI/CD pipelines using GitHub Actions, Azure DevOps and modern DevSecOps practices.
• Working knowledge of infrastructure monitoring, logging, application telemetry and observability tools.
• Experience integrating enterprise applications through REST APIs, Microsoft Graph APIs, SharePoint services and cloud data platforms.
• Familiarity with Microsoft Fabric, Snowflake and Power BI integration architectures.
• Strong understanding of cloud security principles including RBAC, Managed Identity, Key Vault, secret management and secure application design.
• Knowledge of scalable application architecture, distributed systems, performance optimization and reliability engineering.
• Professional proficiency in English.

Nice to have

• Master's Degree or higher in Computer Science, Cloud Computing, Artificial Intelligence, Machine Learning or related technical discipline.
• Experience implementing enterprise AI platforms, AI Centers of Excellence or cloud-based AI transformation initiatives.
• Experience deploying and supporting AI workloads in regulated industries such as healthcare, life sciences or medical technology.
• Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform, Bicep or equivalent cloud automation frameworks.
• Experience with multi-agent orchestration frameworks, autonomous AI systems and advanced LLM application architectures.
• Knowledge of Responsible AI, model evaluation frameworks, enterprise governance, compliance and risk management practices.
• Passion for innovation, continuous learning and solving complex cloud and AI engineering challenges.

Details

• Work location: Hybrid, Bangalore, Karnataka, India.
• Domestic travel may include up to 20%.
• May be required to enter healthcare or other third-party facilities, which may require licenses, vaccinations or other credentials (prerequisites to entry).