Specialist - Architecture

Role Purpose

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

Key Responsibilities

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

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

Develop and govern automation using APIs, Python, PowerShell, Ansible, Terraform, workflow engines, runbooks, and low-code platforms

Implement event correlation, noise reduction, anomaly detection, predictive insights, automated remediation, ticket enrichment, routing, and closed-loop operations

Support cloud and on-premises 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 AI-enabled 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, conduct code review, enable CI/CD testing, build reusable modules, produce technical documentation, and ensure production support readiness

Partner with operations towers to identify high-volume opportunities, quantify benefits, prioritize the backlog, and drive measurable adoption

On-Premises Cloud Scope

On-premises scope includes data centers, branch/campus locations, physical and virtual infrastructure, enterprise tools, local connectivity, operational processes, and legacy-regulated workloads

Cloud scope includes AWS, Microsoft Azure, Google Cloud, SaaS cloud-native monitoring and security identity integration, private connectivity, resilience, tagging, cost awareness, and shared-responsibility controls

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

Technical Functional Skill Matrix

Skill Area    Expected Capability    Priority

Automation   Python, PowerShell, Ansible, Terraform, REST APIs, JSON, YAML, Git, testing and CI/CD    Mandatory

Observability AIOps   Metrics, logs, traces, events, correlation, topology, anomaly detection, dashboards, and engineering    Mandatory

IT operations tools   Monitoring, ITSM integrations, schedulers, discovery, orchestration, reporting, and virtual-agent ecosystems    Mandatory

AI governance   Responsible use, data security, human-in-the-loop evaluation, auditability, and operational risk control    Mandatory

Hybrid platforms   Windows, Linux, virtualization, cloud services, containers, networks, databases, and identity fundamentals    Preferred

Product ownership   Roadmap, backlog, service levels, vendor management, adoption benefits realization, and stakeholder engagement    Mandatory

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 enterprise-scale environments with formal ITSM, security audit, change, and service-level controls

Strong analytical troubleshooting, documentation, presentation, and stakeholder-management capabilities

Ability to work across distributed teams and participate in planned changes, incident bridges, and on-call support when required

Preferred Certifications

Cloud architect, DevOps certification

Automation IaC certification

Observability AIOps platform certification

Responsible AI or security certification

Success Measures KPIs

Automation hours saved and adoption

Event noise reduction and auto-remediation rate

Tool availability and integration reliability

Change success, defect leakage, and time to deploy

AI automation control compliance and realized value

Behavioral Competencies

Customer and business outcome orientation

Ownership, accountability, and disciplined follow-through

Clear communication during normal operations and high-severity 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 architecture design discussion, production troubleshooting scenarios, operational governance examples, cloud-onpremises integrat