AI Cloud Engineer

Solventum

AI Cloud Engineer building secure, scalable Azure AI and Generative AI platforms. Enabling Solventum’s healthcare innovations through cloud infrastructure, integrations, and automation.

Posted 8/4/2026full-timeBangalore • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying cloud-native AI solutions, with a strong focus on Azure services, API development, and compliance with security and regulatory standards. Proficient in implementing CI/CD pipelines and managing scalable AI application infrastructure.

Highest-signal resume keywords

Azure Cloud ServicesPython ProgrammingGenerative AI SolutionsCI/CD Pipeline ImplementationAPI Development Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonFastAPIAzure OpenAIAzure Container AppsDockerCI/CD PipelinesREST APIsInfrastructure MonitoringPerformance OptimizationDistributed Systems

Tools & Technologies

Microsoft GraphSharePointMicrosoft FabricSnowflakePower BIGitHub ActionsAzure DevOpsTerraformBicepObservability Tools

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Related Technical Discipline

Industry Keywords

Cloud-Native AI SolutionsGenerative AIAI-Powered AutomationEnterprise SecurityRegulated Industries

Tech Stack

Tools & technologies

AzureCloudCyber SecurityDistributed SystemsDockerPythonTerraformVault

About the role

Key responsibilities & impact

Design, develop, and deploy cloud-native AI solutions from proof of concept through production deployment
Build and manage scalable AI application infrastructure using Azure cloud services, containerized architectures, and modern software engineering practices
Implement and support Generative AI, Retrieval-Augmented Generation, Agentic AI, and AI-powered automation solutions across enterprise business functions
Develop and maintain API-driven integrations with Microsoft Graph, SharePoint, Microsoft Fabric, Snowflake, Power BI, and other business applications
Collaborate with AI engineers, data engineers, architects, cybersecurity teams, and business stakeholders
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
Ensure compliance with enterprise security, governance, responsible AI, and regulatory requirements
Contribute to platform standardization, architecture reviews, technical documentation, and cloud engineering best practices
Work with multi-agent orchestration frameworks, autonomous AI systems, and advanced LLM application architectures

Requirements

What you’ll need

Bachelor’s Degree or higher in Computer Science, Engineering, Data Science, Mathematics, Information Technology, or related technical field and 5–7 years of job-related experience, or High School Diploma/GED and 10 years of the same 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 services
Experience building and deploying enterprise-scale AI/ML and Generative AI solutions in cloud environments
Working knowledge of 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 required
Healthcare or third-party facilities may require licenses, vaccinations, and/or other prerequisites to entry
Master’s Degree or higher in a related technical discipline is an additional qualification
Experience with enterprise AI platforms, AI Centers of Excellence, regulated industries, Infrastructure as Code tools such as Terraform or Bicep, and cloud-based AI transformation initiatives would be advantageous

Benefits

Comp & perks

Competitive pay and benefits
Programs supporting physical and financial well-being
Up to 20% domestic travel may be included