Lead Infrastructure Engineer-capacity Management

JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

Lead Infrastructure Engineer focused on capacity management within a Corporate Technology Information Management team. Responsibilities include analyzing capacity and performance data, creating reports, identifying hotspots, recommending upgrades, designing and building analytical models for forecasting and risk analysis, delivering automation and tooling, collaborating with stakeholders, and presenting recommendations. Requires formal training/certification in infrastructure engineering, 5+ years of experience, expertise in infrastructure operations (virtual servers, Kubernetes, PCF), data analysis/reporting/visualization (Excel, Tableau, Grafana), capacity management, monitoring/observability tools (BMC Truesight, Dynatrace, AppDynamics), statistical techniques, coding (Java/Python), and time series models (ARIMA, Prophet). Preferred qualifications include experience with agentic AI systems, foundation models, Python, RAG, LangChain, and LangGraph.

What you'd actually do

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.

Skills

Required

infrastructure engineering concepts
infrastructure operations
virtual servers
Kubernetes
Pivotal Cloud Foundry (PCF)
data analysis
reporting
visualization
Excel
Tableau
Grafana
capacity management
capacity models
monitoring tools
observability tools
BMC Truesight
Dynatrace
AppDynamics
statistical techniques
Java
Python
time series models
ARIMA
Prophet

Nice to have

agentic AI systems
foundation models
OpenAI
Gemini
Claude
Grok
RAG
LangChain
LangGraph

What the JD emphasized

5+ years applied experience
Expertise in infrastructure operations
Expertise in data analysis, reporting, and visualization
Experience in capacity management
Experience using monitoring and observability tools
Knowledge of statistical techniques
Experience coding with one or more modern programming languages
Experience developing and applying time series models

Read full job description

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

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