Application Support Engineer (Level 2)
Overview
We are looking for an experienced Application Support Engineer (Level 2) to provide endtoend support for missioncritical applications and services. The ideal candidate will have strong expertise in cloud platforms, containerization, databases, and scripting, with a proactive mindset toward reliability, performance, and continuous improvement.
Key Responsibilities
- Deliver comprehensive support services, including incident and problem resolution, operational requests, and application lifecycle management.
- Ensure high availability and performance of eCommerce fulfillment applications and services.
- Design and implement monitoring, alerting, and observability solutions using Grafana and AppDynamics.
- Continuously monitor system health, performance, and availability.
- Perform system maintenance of Azure Kubernetes Services (AKS).
- Collaborate with development and operations teams to improve system reliability and scalability.
- Conduct root cause analysis and postincident reviews to prevent recurrence.
- Coordinate with external vendors to resolve application issues.
- Participate in oncall rotations and respond to production incidents with urgency and clarity.
- Work on rotating shifts to support 24x7 operations.
- Contribute to strategies and automations that drive team excellence and continuous improvement.
Qualifications
NonNegotiable
- Handson experience in Application Support (Level 2).
- Strong knowledge of Microsoft Azure, Azure Kubernetes Service (AKS), MongoDB, SQL DB, and either Java or Python.
Required
- Bachelor's degree in Information Technology, Computer Science, Engineering, or related field.
- 57 years of experience as a Developer or in Application & Maintenance Support.
- Proficiency in:
- Cloud Platforms: Microsoft Azure, Google Cloud Platform (GCP)
- Operating Systems: Unix/Linux and Windows; Unix shell commands and scripting
- Databases/Data Warehouses: MongoDB, Azure Cosmos DB, SQL, BigQuery
- Query Languages: KQL, LogQL, PromQL
- Monitoring & Observability: Grafana, AppDynamics
- Containerization & Orchestration: AKS, Helm
- Messaging Systems: Kafka
- CI/CD Tools: GitHub Actions, general CI/CD pipelines
- Programming/Scripting: Python, Java
- Data & Analytics Platforms: Databricks
- Workload Automation: Stonebranch
- Infrastructure as Code & Automation: Helm, GitOps practices
- ITSM Tools: ServiceNow
- Experience with incident management, root cause analysis, and Agile frameworks.
- Exposure to AI for anomaly detection, predictive analysis, log/metric analysis, and process improvement.
- Experience integrating AI solutions into processes or systems.
