Cloud & AI Solutions Architect (24741)

Role Description:

• Design architecture for AI/ML solutions (including GenAI) from POC to production
• Lead implementation and integration processes with enterprise systems (APIs, data flows, identity & access)
• Design and build runtime infrastructures for AI models and services on Kubernetes / OpenShift
• Establish CI/CD pipelines, automation, and Infrastructure as Code (IaC) for deployment, scaling, configuration management, and disaster recovery (DR)
• Define standards and guardrails in areas such as security, privacy, data governance, monitoring, and auditability
• Work closely with development, data, security, and infrastructure teams, including writing architecture and design documents

Requirements:

• Proven experience in designing and implementing AI/ML solutions in production environments
• Hands-on experience with Kubernetes and/or OpenShift (deployments, cluster management, networking, permissions)
• Experience working with Public Cloud platforms (AWS / Azure / GCP) – compute, storage, networking, security
• Strong experience with Infrastructure as Code (IaC), especially Terraform (modules, environments, state management, best practices)
• Experience in DevOps practices: CI/CD, GitOps, automation, configuration & version management
• Proficiency in Python for development, automation, or services
• Experience designing and consuming REST APIs (OpenAPI/Swagger, authentication, rate limiting)
• Solid understanding of Linux, networking, and containerization (Docker)

Advantages:

• Experience with MLOps (model lifecycle, model registry, feature store, experiment tracking, monitoring)
• Experience in Generative AI domains (LLMs, RAG, vector databases, prompting, evaluation, observability)
• Experience in cloud security (IAM, secrets management, network policies, Zero Trust)
• Experience with observability tools (Prometheus, Grafana, ELK, OpenTelemetry)
• Experience designing scalable, high-availability systems, including performance optimization and FinOps
• Experience working in complex enterprise environments