Cloud Architect

About the role

The AI, Software & Cloud Architect designs scalable, secure, and business‑aligned technology solutions that blend artificial intelligence, modern software engineering, and cloud platforms. You will work closely with business stakeholders, engineering, security, data, and platform teams to turn business needs into robust architecture patterns and implementation roadmaps.

Key responsibilities

• Design end‑to‑end solution architectures across AI, software applications, data platforms, APIs, and cloud services.
• Define architecture standards, patterns, principles, and reusable reference designs.
• Lead the design of AI‑enabled solutions, including generative AI, machine learning, automation, and analytics‑driven applications.
• Architect scalable cloud‑native platforms using AWS, Azure, GCP, or hybrid environments.
• Guide application modernization with microservices, containers, serverless, event‑driven architecture, and API‑led integration.
• Collaborate with data scientists, ML engineers, and cloud engineers to move AI solutions from prototype to production.
• Ensure solutions meet scalability, availability, performance, resilience, maintainability, and cost‑efficiency requirements.
• Support cloud migration strategies, platform selection, workload assessment, and modernization roadmaps.
• Evaluate emerging AI, software, and cloud technologies and recommend practical adoption.
• Partner with security architects to embed security, privacy, compliance, and responsible AI principles.

Required profile

• Strong experience in solution, software, or enterprise architecture.
• Hands‑on software engineering background with languages such as Java, Python, JavaScript, TypeScript, Go, or C#.
• Proven experience designing cloud solutions on AWS, Azure, GCP, or private cloud platforms.
• Deep knowledge of cloud‑native architecture, microservices, APIs, containers, Kubernetes, serverless, and DevOps practices.
• Understanding of AI/ML solution design, model lifecycle, prompt engineering, MLOps, LLM integration, vector databases, and AI governance.
• Experience with enterprise integration patterns, event streaming, messaging, and API management.
• Strong grasp of architecture documentation, design reviews, and technical decision records.
• Knowledge of data architecture concepts such as data lakes, warehouses, lakehouses, pipelines, and real‑time analytics.

Required skills

• Java
• Python
• JavaScript
• TypeScript
• Go
• C#
• AWS
• Azure
• GCP
• Kubernetes
• Containers
• Serverless
• DevOps
• Microservices
• APIs
• AI/ML
• MLOps
• LLM integration
• Vector databases
• AI governance
• Enterprise integration patterns
• Event streaming
• Messaging
• API management
• Data lakes
• Data warehouses
• Lakehouses
• Data pipelines
• Real‑time analytics