Systems Architect - Cloud AIOps

EPAM Systems; Gurugram District; On-site; INR 4,200,000 - 6,600,000; Full time

Job summary

EPAM Systems is seeking an experienced Systems Architect - Cloud AIOps to design next-gen cloud platforms with AI-driven intelligence at the core. You will shape AI-enabled platform engineering strategies, lead AIOps initiatives, and serve as a senior technical authority across modernization programs.

The role covers cloud infrastructure and cloud-native environments, including landing zones, Kubernetes, service mesh, and AI-assisted decision support. Strong English communication is required.

Qualifications

• 13-20 years of cloud platform architecture and engineering experience.
• Cloud Infrastructure path: landing zones, VPC/VNet design, and security & IAM, with hybrid/multi-cloud connectivity.
• Cloud Native path: Kubernetes platforms (EKS/AKS), microservices modernization, and service mesh (Istio/Linkerd), incl. GitOps and container security.
• Infrastructure as Code with Terraform, Ansible, and CloudFormation or ARM/Bicep.
• CI/CD and platform automation with Jenkins, GitHub Actions, and GitLab CI.
• Automation scripting with Python, Shell, and PowerShell.
• Observability stacks: Prometheus, Grafana, ELK/EFK; OpenTelemetry, Datadog, AppDynamics, New Relic.
• Strong SRE foundations: SLIs/SLOs, error budgets, incident automation, postmortems.
• AIOps capabilities: event correlation across telemetry, anomaly detection, automated remediation, predictive alerting.
• Understanding of RAG architectures for operational knowledge retrieval.
• Proven experience leading modernization programs and defining platform roadmaps.
• Ability to assess legacy vs cloud environments and define AI-enabled target architectures.
• Strong English communication skills (B2 level or higher).

Responsibilities

• Architect and evolve cloud platforms (AWS or Azure) with AI as a design principle.
• 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.

Skills

Cloud architecture

AWS / Azure

Kubernetes platforms

Terraform

CI/CD pipelines

SRE fundamentals

Python / Shell

Observability stacks

AIOps capabilities

RAG architectures

LLM pipelines

English Proficiency

Tools

Terraform

Ansible

CloudFormation

ARM / Bicep

Jenkins

GitHub Actions

GitLab CI

Prometheus

Grafana

ELK/EFK

OpenTelemetry

Datadog

New Relic

AppDynamics

Job description

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)