Systems Architect - Cloud AIOps

Summary

Senior architect designing and evolving AI-driven cloud platforms on AWS or Azure, embedding AIOps, observability, SRE principles, and RAG-based operational intelligence across enterprise modernization programs.

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)

Benefits

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

Benefit package:

  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)

See also

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