Lead Infrastructure Engineer-Capacity Management
Chase
Lead Infrastructure Engineer-Capacity Management
Lead our collaborative and innovative team, where your expertise in capacity management will help shape the future of our technology. We value diverse perspectives and are committed to fostering an inclusive environment where everyone can thrive and contribute to impactful solutions.
As a Lead Infrastructure Engineer-Capacity Management at JPMorgan Chase within the Corporate Technology Information Management team, you utilize strong knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Apply your technical knowledge and problem-solving methodologies across multiple applications of moderate scope.
Job responsibilities
- Analyze capacity and performance data across infrastructure and applications
- Create capacity management reports, identify infrastructure hotspots, and recommend upgrades/downgrades
- Design, build, and maintain analytical models for capacity forecasting, risk analysis, and other ad-hoc business needs.
- Deliver increased automation and tooling capability across capacity management.
- Collaborate with internal stakeholders to gather and understand capacity requirements.
- Present modeling recommendations to technical and non-technical audiences.
Required qualifications, capabilities, and skills
- Formal training or certification in infrastructure engineering concepts, and 5+ years applied experience
- Expertise in infrastructure operations and technical infrastructure including virtual servers, Kubernetes, and Pivotal Cloud Foundry (PCF)
- Expertise in data analysis, reporting, and visualization, including Excel, Tableau, and Grafana
- Experience in capacity management and designing and implementing capacity models to forecast resource needs and optimize data platform performance
- Experience using monitoring and observability tools such as BMC Truesight, Dynatrace, AppDynamics, or similar platforms to analyze system performance and ensure reliability
- Knowledge of statistical techniques to analyze data and support decision-making
- Experience coding with one or more modern programming languages such as Java or Python
- Experience developing and applying time series models such as ARIMA, Prophet, or similar methods to forecast trends and patterns in data
- Preferred qualifications, capabilities, and skills
- Experience building agentic AI systems that automate complex workflows, and leveraging foundation models (OpenAI, Gemini, Claude, Grok, etc.)
- Experience with Python, RAG, LangChain, LangGraph, or similar AI frameworks
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