Specialist - Architecture

LTM; Navi Mumbai; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

LTM in Navi Mumbai invites an senior engineering leader to drive automation, AIOps observability, and IT operations across hybrid infrastructure. You will own monitoring, event management, orchestration, and automation tooling while ensuring secure, auditable practices.

You will design integration architectures, data flows, and release processes, develop automation using modern runtimes, and mentor teams across on-prem and cloud environments.

Qualifications

• Bachelor's degree in engineering, computer science, information technology, or related discipline.
• 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.

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 and recovery.
• Develop 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 and closed-loop operations.
• Support 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/output handling, auditability and rollback.
• Manage models or AI-enabled features used for operations without exposing sensitive data; monitor quality, drift, false positives and risk.
• Troubleshoot integrations, agents, collectors, APIs, credentials, queues, certificates, data pipelines, dashboards, automations and performance issues.
• Maintain source control, code review, CI/CD, testing, reusable modules, technical documentation, ownership and production support readiness.
• Partner with operations towers to identify opportunities, quantify benefits, prioritize backlog and drive adoption.

Skills

Automation

Python

PowerShell

Ansible

Terraform

REST APIs

JSON

YAML

Git

CI/CD

Observability

AIOps

Monitoring

ITSM

Integrations

Schedulers

Discovery

Orchestration

Reporting

Virtual Agent

Windows

Linux

Virtualization

Cloud Services

Containers

Networks

Databases

Identity

Roadmap

Backlog

Service Levels

Vendor Management

Adoption

Benefits Realization

Stakeholder Engagement

Education

Bachelor's degree in engineering / CS / IT

Tools

Windows

Linux

Virtualization

Cloud Services

Containers

Networks

Databases

Identity Fundamentals

Job description

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 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

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

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