Systems Architect - Cloud AIOps
We are seeking an experienced Systems Architect - Cloud AIOps to design and evolve next-generation cloud platforms where AI-driven intelligence is embedded as a foundational design principle. In this role, you will shape AI-enabled platform engineering strategies, lead AIOps architecture initiatives, and serve as a senior technical authority guiding enterprise modernization programs across cloud infrastructure and cloud-native environments.
Responsibilities
- Architect and evolve cloud platforms (AWS or Azure) where AI-driven intelligence is a foundational design principle, not an afterthought
- Define and drive AI-enabled platform engineering strategy, integrating observability, telemetry pipelines, intelligent alerting, predictive insights, and automation
- Lead the design of AIOps architectures that combine monitoring data, logs, metrics, traces, and operational knowledge to support proactive operations
- Embed SRE principles (SLIs, SLOs, error budgets) into platform design and enable AI-assisted reliability management
- Serve as a senior technical authority in customer-facing engagements, architecture workshops, and RFP/RFI responses, articulating AI-driven platform value
- For Cloud Infrastructure-led engagements: architect AI-ready landing zones, networking, IAM, hybrid connectivity, DR, and cost governance
- For Cloud Native-led engagements: architect Kubernetes platforms, modernization initiatives, and cloud-native runtime environments designed for intelligent operations
- Design and integrate AI-assisted operational knowledge systems, including RAG-based architectures, to accelerate root cause analysis and decision support
- Collaborate with data and ML teams to consume AI/ML capabilities for operations (anomaly detection, automated RCA, predictive capacity insights)
- Provide architectural guidance on LLM, vector stores, and RAG pipelines as platform components for operational and reliability use cases
- Mentor architects and senior engineers, establishing AI-aware platform engineering standards across the organization
Requirements
- 13-20 years of experience in cloud platform architecture and engineering
- For the Cloud Infrastructure path: expertise in enterprise landing zones, VPC/VNet design, and security & IAM, along with hybrid/multi-cloud connectivity
- For the Cloud Native path: proficiency in Kubernetes platforms (EKS/AKS), microservices modernization, and service mesh (Istio/Linkerd), including GitOps and container security
- Background in Infrastructure as Code using Terraform, Ansible, and CloudFormation or ARM/Bicep
- Skills in CI/CD and platform automation with Jenkins, GitHub Actions, and GitLab CI
- Competency in automation and integration scripting with Python, Shell, and PowerShell
- Familiarity with observability stacks such as Prometheus, Grafana, and ELK/EFK, as well as OpenTelemetry, Datadog, AppDynamics, and New Relic
- Strong SRE foundations covering SLIs/SLOs, error budgets, incident automation, and postmortems
- Expertise in AIOps capabilities, including event correlation across telemetry sources, anomaly detection on metrics/logs/traces, automated remediation with intelligent runbooks, and predictive alerting and capacity insights
- Understanding of RAG architectures for operational knowledge retrieval and AI-assisted decisioning
- Proven experience leading platform-led modernization programs and influencing platform roadmaps at enterprise and portfolio levels
- Capability to assess legacy and cloud environments and define AI-enabled target platform architectures, combining platform engineering, AI capabilities, and operational excellence
- Strong English communication skills (B2 level or higher)
