Establish trusted advisor relationships with senior and executive-level stakeholders
Design detailed, well-documented hybrid cloud and AI-enabled solutions that address customer requirements and RFPs, in close collaboration with sales teams
Lead workshops to gather business, technical, and data-related requirements across stakeholders
Facilitate goal-aligned discussions and propose architectures aligned with HPE and partner portfolios
Provide strategic guidance on hybrid cloud, AI, and data platform adoption, aligned with business objectives
Define and communicate hybrid cloud and AI adoption roadmaps, including key milestones and dependencies
Develop cost models, including AI workload cost estimation, and recommend strategies to optimize infrastructure and cloud spend
Design end-to-end architectures integrating on-premises infrastructure, cloud platforms, and AI/ML services
Support and lead implementation efforts, ensuring security, compliance, ethical AI principles, and best practices
Oversee migration of applications, data, and AI workloads between on-premises and cloud environments
Collaborate with data and application teams to enable AI-ready platforms, including data pipelines, model hosting, and inferencing capabilities
Monitor and optimize hybrid cloud and AI platform performance, leveraging automation and AIOps where applicable
Stay current on emerging trends in AI, machine learning, cloud-native platforms, and automation, and contribute to the technical community.

7+ years of experience as a Cloud Engineer, Cloud Architect, or Infrastructure Architect
Strong background in hybrid cloud, IaaS, PaaS, DevOps, and CI/CD
Solid market knowledge of IT consulting services related to cloud and AI transformation
Hands-on experience with containers, Kubernetes, and microservices
Knowledge of Linux and Windows operating systems
Solid understanding of AI/ML architecture concepts such as: Model training vs. inferencing, Data pipelines and feature stores, GPU/accelerator-based workloads
Familiarity with MLOps principles, automation, and lifecycle management of Private Cloud solutions
Understanding of IT infrastructure components (compute, storage, networking, virtualization) and their role in business workloads
Proficiency in infrastructure and solution architecture methodologies
Familiarity with ITIL / ITSM frameworks (preferred)
Experience in large-scale enterprise environments is a strong advantage.
Fluent in both the local language and English.

Delivery Solution Architect – Hybrid Cloud, Infrastructure, AI Solutions

Key skills