Specialist - Architecture

Role Purpose

Lead the support engineering integration and controlled adoption of automation AIOps observability IT operations tools virtual agents and operational AI solutions across hybrid infrastructure

Key Responsibilities

Own operational tools covering monitoring event management AIOps automation orchestration job scheduling ITSM integrations discovery reporting and virtual agents

Design support models architecture integrations data flows access controls environments release processes backup recovery monitoring and capacity for the toolchain

Develop and govern automation using APIs Python PowerShell Ansible Terraform workflow engines runbooks and lowcode platforms

Implement event correlation noise reduction anomaly detection predictive insights automated remediation ticket enrichment routing and closedloop operations

Support cloud and onpremises telemetry collection across servers databases networks storage applications containers endpoints and business services

Establish safe AI practices including approved use cases human oversight access control data classification prompt and output handling auditability evaluation and rollback

Manage models or AIenabled features used for operations without exposing sensitive data monitor quality drift false positives and operational risk

Troubleshoot integrations agents collectors APIs credentials queues certificates data pipelines dashboards automations and performance issues

Maintain source control code review CICD testing reusable modules technical documentation ownership and production support readiness

Partner with operations towers to identify highvolume opportunities quantify benefits prioritize backlog and drive measurable adoption

OnPremises Cloud Scope

Onpremises scope data centers branchcampus locations physical and virtual infrastructure enterprise tools local connectivity operational processes and legacyregulated workloads

Cloud scope AWS Microsoft Azure Google Cloud SaaS cloudnative monitoring and security identity integration private connectivity resilience tagging cost awareness and sharedresponsibility controls

Hybrid scope consistent governance service mapping monitoring access configuration automation recovery reporting and support handoffs across both environments

Technical Functional Skill Matrix

Skill AreaExpected CapabilityPriority

AutomationPythonPowerShell Ansible Terraform REST APIs JSONYAML Git testing and CICDMandatory

Observability AIOpsMetrics logs traces events correlation topology anomaly detection dashboards and engineeringMandatory

IT operations toolsMonitoring ITSM integrations schedulers discovery orchestration reporting and virtualagent ecosystemsMandatory

AI governanceResponsible use data security humanintheloop evaluation auditability and operational risk controlMandatory

Hybrid platformsWindowsLinux virtualization cloud services containers networks databases and identity fundamentalsPreferred

Product ownershipRoadmap backlog service levels vendor management adoption benefits realization and stakeholder engagementMandatory

Required Qualifications Experience

9 to 12 years of relevant experience including ownership of complex enterprise services and production support

Bachelors degree in engineering computer science information technology or a related discipline equivalent practical experience may be considered

Demonstrated experience in enterprisescale environments with formal ITSM security audit change and servicelevel controls

Strong analytical troubleshooting documentation presentation and stakeholdermanagement capabilities

Ability to work across distributed teams and participate in planned changes incident bridges and oncall support when required

Preferred Certifications

Cloud architectDevOps certification

AutomationIaC certification

ObservabilityAIOps platform certification

Responsible AI or security certification

Success Measures KPIs

Automation hours saved and adoption

Event noise reduction and autoremediation rate

Tool availability and integration reliability

Change success defect leakage and time to deploy

AIautomation control compliance and realized value

Behavioral Competencies

Customer and business outcome orientation

Ownership accountability and disciplined followthrough

Clear communication during normal operations and highseverity incidents

Collaboration across towers vendors and geographies

Continuous learning knowledge sharing and improvement mindset

Risk awareness and sound judgment under pressure

Screening Guidance

Candidates should be assessed through a combination of architecturedesign discussion production troubleshooting scenarios operational governance examples cloudonpremises integrat