Systems Architect - Cloud AIOps

Office in India: Gurugram,

Systems Architecture

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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)