Cloud Solution Architect

Introduction

The Cloud Solution Architect is responsible for designing, guiding, and governing secure, cost-efficient, and target-aligned AWS cloud infrastructure for the enterprise Data & AI ecosystem, covering data platforms, storage capabilities, AI/ML solutions, infrastructure automation, and cloud cost optimization.

Responsibilities

• Cloud Architecture for Data & AI Platforms: Designs and evolves the cloud infrastructure and platform architecture supporting the enterprise Data Lakehouse (AWS S3, Redshift, Glue, Athena, EMR), real-time streaming backbones (Amazon MSK / Kafka), and analytical databases.
• Enterprise AI & MLOps Infrastructure: Architects secure, scalable cloud runtimes for AI and machine learning workloads, including GPU/accelerator compute clusters, model training/fine-tuning pipelines, low-latency LLM inference endpoints (Amazon SageMaker, AWS Bedrock), Vector Databases, Feature Stores, and RAG retrieval infrastructure.
• Alignment with Cloud & Infrastructure Lead Architect:
• Enforces enterprise cloud foundation baselines, AWS multi-account landing zone standards, centralized IAM, VPC networking, Transit Gateway routing, and hybrid connectivity (Direct Connect to on-prem data centers / CETIN).
• Implements standardized container platform patterns (AWS EKS), cluster autoscaling (Karpenter), multi-tenancy, service mesh, and container security guardrails across data and AI workloads.
• Alignment with Data & AI Lead Architect: Translates the Data & AI Layer Reference Architecture, Enterprise Data Model (EDM), and semantic patterns into robust, production-grade cloud infrastructure blueprints and deployment models.
• Cloud Security, Zero Trust & Data Isolation: Implements cloud security controls including KMS customer-managed key encryption at rest and in transit, private VPC endpoints (AWS PrivateLink), fine-grained data access controls (AWS Lake Formation, RBAC/ABAC), network segmentation, and secure data egress/ingress controls compliant with GDPR and enterprise security baselines.
• FinOps & Cloud Cost Optimization: Owns cloud unit economics and cost management for analytical and AI workloads. Establishes compute/storage autoscaling policies, spot/graviton/reserved instance strategies, intelligent S3 storage tiering, query cost attribution, and resource lifecycle automation.
• Infrastructure as Code (IaC) & DataOps/MLOps CI/CD: Establishes reusable Infrastructure-as-Code templates (Terraform, OpenTofu, Helm), GitOps deployment patterns (ArgoCD), and automated CI/CD pipelines for provisioning data platform services and AI model serving environments.
• High Availability, Disaster Recovery & Resilience: Designs backup, snapshotting, cross-region replication, and disaster recovery architectures meeting enterprise RPO/RTO targets for mission-critical analytical datasets and AI services.
• Architecture Governance & ARB Defense: Authors cloud infrastructure HLDs, formulates Architecture Decision Records (ADRs/KDDs), and defends cloud data/AI solutions at the Architecture Review Board (ARB) and Target Architecture Board (TAB).
• Delivery & Operational Readiness: Partners closely with data platform engineers, site reliability engineers (SRE), and delivery squads to ensure seamless deployment, automated observability (CloudWatch, OpenTelemetry), alerting, and operational handover

Requirements

• Bachelor’s or Master’s degree in Computer Science, Cloud Computing, Software Engineering, Systems Engineering, or related technical field.
• 4+ years of proven experience as a Cloud Solution Architect, Cloud Infrastructure Architect, or Senior Cloud Data Engineer designing large-scale distributed systems on public cloud platforms.
• In-depth architectural mastery of Amazon Web Services (AWS) core infrastructure and data/AI services: S3, EKS, Redshift (Serverless & Provisioned), EMR, Glue, Athena, MSK, SageMaker, Bedrock, IAM, VPC, KMS, Transit Gateway.
• Relevant professional cloud certifications (e.g., AWS Certified Solutions Architect – Professional, AWS Certified Data Analytics – Specialty, or AWS Certified Machine Learning – Specialty).
• Deep understanding of Kubernetes and container orchestration (AWS EKS, Karpenter, container networking, Helm charts, GPU scheduling for AI/ML workloads).
• Strong background in Infrastructure as Code (Terraform), GitOps, DevSecOps automation, and configuration management.
• Solid experience with FinOps methodologies, cloud cost observability, compute right-sizing, and storage lifecycle management in petabyte-scale data environments.
• Strong grasp of cloud security principles, network isolation, private endpoints, encryption key management, and regulatory compliance (GDPR, ISO 27001).
• Familiarity with telecommunications data architectures (high-throughput CDR streams, CVM, BSS/OSS integration, hybrid cloud network demarcation with partners like CETIN) is an advantage.
• Ability to work effectively in cross-functional agile teams and international vendor environments.
• Excellent technical documentation, presentation, and stakeholder collaboration skills in English and Hungarian.

Onsite

• 2-3 days / week on-site in Törökbálint