Job Summary

Role Summary The APM Engineer will be responsible for implementing, administering, and optimizing enterprise Application Performance Monitoring and Observability capabilities using Splunk AppDynamics and Splunk Observability Cloud. The role will focus on end-to-end application visibility, application/service performance, distributed tracing, infrastructure monitoring, Kubernetes observability, real-user monitoring, synthetic monitoring, alerting, and proactive identification of performance degradation. The engineer will work closely with Application, Cloud, Infrastructure, DevOps/SRE, Network, Database, Event Management, Incident Management, and ITSM teams to improve application reliability and reduce MTTD and MTTR.

Key Responsibilities

Key Responsibilities 1. AppDynamics Administration & Engineering Install, configure, administer, upgrade, and troubleshoot AppDynamics Controllers and Agents. Configure APM monitoring for Java, .NET, Node.js, and other supported application environments. Configure Business Applications, Tiers, Nodes, Business Transactions, Health Rules, Policies, Actions, and Dashboards. Identify application performance bottlenecks using transaction-level monitoring and diagnostics. Perform application-flow and dependency analysis across application tiers, databases, APIs, middleware, and external services. Configure appropriate baselines and thresholds to minimize false-positive alerts. 2. Splunk Observability Cloud Implement and support Splunk Observability Cloud capabilities including: Application Performance Monitoring Infrastructure Monitoring Real User Monitoring Synthetic Monitoring Log Observer / log correlation Configure detectors, dashboards, charts, alerts, metrics, dimensions, and service-level monitoring. Implement distributed tracing for microservices and cloud-native applications. Enable correlation across metrics, traces, and logs for faster troubleshooting. Implement and support OpenTelemetry-based instrumentation and telemetry collection. 3. Application Performance Monitoring Monitor critical business applications for availability, response time, throughput, error rate, and resource utilization. Analyze: Slow transactions Application errors API latency Database response time External service calls JVM/.NET performance Memory and CPU utilization Application dependencies Establish dynamic baselines and intelligent alerting. Identify recurring performance issues and recommend corrective actions. 4. Cloud & Kubernetes Observability Implement monitoring for applications hosted across: Microsoft Azure AWS Kubernetes Virtual Machines Containers Hybrid infrastructure Monitor Kubernetes clusters, nodes, pods, containers, namespaces, workloads, and services. Configure telemetry collection using OpenTelemetry Collector and relevant Splunk agents. Monitor cloud-native applications, microservices, APIs, and serverless workloads where applicable. Correlate infrastructure health with application performance issues. 5. End-to-End Observability Develop observability across the application stack: User Experience → Application → API → Microservices → Database → Infrastructure → Cloud/Kubernetes Enable correlation across logs, metrics, traces, and application transactions. Build dashboards showing business-service and application health. Develop service dependency views to support faster fault isolation. Partner with application and infrastructure teams to establish meaningful SLIs, SLOs, and alerting thresholds. 6. Incident & Problem Management Provide APM/observability support during P1/P2 and Major Incidents. Assist Incident Management teams with application performance analysis and fault isolation. Analyze traces, transactions, metrics, logs, and dependency information to identify potential failure points. Support RCA investigations with relevant performance evidence and timelines. Identify monitoring gaps following critical incidents and implement improvements. 7. Event Management & ITSM Integration Integrate AppDynamics / Splunk Observability alerts with Splunk ITSI and ServiceNow or equivalent platforms. Ensure alerts contain sufficient context for Event Management and Operations teams. Support automated incident creation for validated alert conditions. Work with Event Management teams on: Alert normalization Deduplication Correlation Suppression Severity mapping Event enrichment Identify opportunities for event-triggered automation and self-healing. 8. Performance Optimization Perform application performance analysis and trend reviews. Identify abnormal response time, resource saturation, error patterns, and dependency issues. Support capacity planning using historical performance metrics. Provide recommendations to Application, DevOps,

Skill Requirements

Technical Skills Mandatory Area Required SkillsAPM AppDynamics Observability Splunk Observability Cloud Telemetry OpenTelemetry APM Concepts Business Transactions, Service Maps, Tracing Cloud Azure and/or AWS monitoring Containers Kubernetes / Docker observability Monitoring Metrics, Logs, Traces Integration REST APIs, Webhooks OS Linux / Windows fundamentals Troubleshooting Application and infrastructure performance analysis Preferred Splunk Enterprise / Splunk ITSI ServiceNow Dynatrace / Datadog / New Relic exposure Azure Monitor / Application Insights AWS CloudWatch Prometheus / Grafana Terraform / Ansible Python / PowerShell / Shell scripting CI/CD and DevOps tooling

Other Requirements

Functional Knowledge The candidate should have a solid understanding of: Application Performance Management Observability principles Metrics, Events, Logs and Traces Distributed tracing OpenTelemetry Microservices architecture Kubernetes and containers REST APIs Application dependency mapping Incident and Problem Management Performance troubleshooting SLI/SLO concepts ITIL Event, Incident and Change Management For a Pharma/Life Sciences environment, exposure to GxP, validated systems, audit controls, controlled change processes, and regulated production environments would be advantageous.