AVP- Technology Infrastructure

Job Title: Assistant Vice President – Technology Infrastructure & Applications ObservabilityLocation: NoidaReports To: Vice PresidentExperience: 12+ years in Technology Infrastructure / Observability / SRE rolesDepartment: Global TechnologyJob OverviewWe are seeking a dynamic and experienced Assistant Vice President (AVP) to lead our Technology Infrastructure and Applications Observability Practice . The AVP will oversee a multidisciplinary team across Operations, Site Reliability Engineering (SRE), Engineering, and Client Engagement , driving excellence in service delivery and leveraging AI-powered Observability to enhance performance, resilience, and business value.The ideal candidate will bring a strong mix of technical depth , strategic thinking , and executive communication , along with a passion for showcasing the business impact of infrastructure insights through data storytelling and intelligent dashboards .Key ResponsibilitiesLeadership & StrategyLead the Observability Practice spanning infrastructure and application monitoring , log & trace analytics , AIOps , and SRE automation .Develop and drive the roadmap for next-gen observability leveraging AI/ML , causal analysis , and predictive intelligence .Collaborate with CIO, platform, and application teams to align observability strategies with business outcomes.Operations & SREManage end-to-end operations for Network and Cloud Infrastructure and ensure key KPIs and SLAs are met as per the ITSM practice on SNOWDrive effective Change Management from overall Monitoring Ops standpointManage real-time monitoring, incident response, and proactive alerting for critical infrastructure and applications.Ensure key KPIs like uptime, latency, Traffic, Errors, Saturation are met as per MSAs and Business requirementsEnsure all new devices, VMs, Cloud Resources, Models, Apps (SaaS, PaaS, IaaS, On-premise) are onboarded for monitoring during post provisioning.Establish and refine SRE principles to improve reliability, reduce toil, and enforce SLAs/SLOs.Drive root cause analysis (RCA), resilience testing, and postmortems.Ensure End user incidents are in check and any deviation w.r.t User Experience is worked uponEngineering & InnovationOversee the build-out of observability pipelines and integrations (e.g. with Datadog).Innovate with AI/ML-based anomaly detection , automated remediation , and observability-as-code .Influence platform instrumentation and telemetry design across environments (on-prem, cloud, hybrid).Client & Stakeholder EngagementServe as a strategic advisor and partner to business stakeholders, product leaders, and client teams.Own the design and delivery of Executive Dashboards , Health Summaries , and Business Impact Reports .Ensure observability solutions reflect client pain points and deliver measurable improvements.Skills and QualificationsTechnical ExpertiseSolid knowledge of Technology Infrastructure (Servers, Networks, Cloud), Application architecture, and modern observability stacks.Knowledge of tools and technology like:ITSM - ServiceNowEnd User - Systrack, NetSkope, CrowdStrike etc.Network NMS, Aviatrix, PaloAlto FW, Arista Switches, Wi-fi tech etc.Servers and Cloud - SCOM, Cloudwatch etc.Contact Center – SoliCall, Operata, AppNeta etc.Observability Platforms like DataDog, Dynatrace, NewRelic etc.Experience with AI for Observability , AIOps platforms, and large-scale monitoring/log management systems.Familiarity with cloud-native ecosystems (AWS/GCP/Azure), containerization (Kubernetes, Docker), and CI/CD integration.Leadership and CommunicationProven ability to lead cross-functional teams across geographies.Strong executive presence with excellent verbal, written, and presentation skills .Ability to simplify technical concepts into business-aligned narratives.Business & Analytical AcumenData-driven mindset with ability to connect metrics with operational and financial impact.Experience in creating value stories , business cases, and customer success narratives.PreferredCertifications in SRE, ITIL, or Observability tools.Exposure to data science, AI/ML models, or advanced analytics projects is a plus.