Lead the engineering and operation of enterprise infrastructure monitoring platforms across Linux, Windows, network, hybrid-cloud, and on-premises environments. Build observability integrations, telemetry collection, dashboards, alerting, automation, and infrastructure-as-code workflows. Improve signal quality, event-to-incident processes, platform resilience, and operational reliability through baselining, noise reduction, RCA, and SLO alignment. Partner with infrastructure, application, and SRE teams while applying secure, auditable AI-assisted engineering practices.
Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies.
As a Lead Infrastructure Engineer at JPMorgan Chase within Enterprise Technology Infrastructure Platforms Monitoring team, you will help build and operate a strategic, market-leading Infrastructure Monitoring platform that strengthens critical service resilience and delivers trusted operational insights. You will be a hands-on technical contributor on an high-performing agile team, building secure, stable, and scalable observability solutions—turning telemetry into actionable insights, modernizing event-to-incident workflows, enabling automation and AIOps-driven reliability improvements aligned to the firm’s business objectives.
Job responsibilities
As a Lead Infrastructure Engineer at JPMorgan Chase within Enterprise Technology Infrastructure Platforms Monitoring team, you will help build and operate a strategic, market-leading Infrastructure Monitoring platform that strengthens critical service resilience and delivers trusted operational insights. You will be a hands-on technical contributor on an high-performing agile team, building secure, stable, and scalable observability solutions—turning telemetry into actionable insights, modernizing event-to-incident workflows, enabling automation and AIOps-driven reliability improvements aligned to the firm’s business objectives.
Job responsibilities
- Engineer, operate, and continuously improve the firm’s Infrastructure Monitoring platforms, ensuring availability, performance, scalability, and security.
- Build and run enterprise-grade Infrastructure Monitoring capabilities across Linux, Windows, and complex Network estates, including platform-level onboarding and lifecycle management.
- Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
- Design and implement platform services, integrations, and telemetry collection across metrics, logs, events, including OpenTelemetry collection patterns where applicable.
- Develop and maintain standardized onboarding patterns (agents/collectors, configurations, dashboards, alert policies) to accelerate safe adoption at scale.
- Improve monitoring signal quality and usability through baselining, threshold strategy, noise reduction, enrichment, and topology/context alignment.
- Develop secure, high-quality automation and production code; review, debug, and improve code/configuration written by others.
- Automate platform operations and reduce toil through scripting and CI/CD-driven configuration management; implement infrastructure-as-code deployment patterns
- Manage & maintain production health for the monitoring platform: lead triage, perform RCA, and deliver preventative engineering and resilience improvements.
- Partner with infrastructure, application, and SRE teams to align platform capabilities to SLIs/SLOs, operational readiness, and continuous improvement goals.
- Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
Required qualifications, capabilities, and skills
- Formal training or certification on infrastructure engineering concepts and 5+ years applied experience
- Proficiency with enterprise operating systems (Linux and/or Windows), including administration, troubleshooting, performance analysis, and operational best practices within regulated production environments.
- Proven hands-on experience delivering and operating enterprise-scale Infrastructure Monitoring solutions across Linux and Windows estates
- Solid understanding and hands-on implementation of observability and telemetry concepts, including metrics, logs, and events, with experience using OpenTelemetry collection patterns and integrating telemetry into Downstream components
- Proficiency in automation and engineering practices, including scripting and development with Python, Ansible, PowerShell / Bash, and applying CI/CD-driven workflows for controlled, secure, and repeatable change management. Experience developing, reviewing, debugging, and maintaining secure, high-quality production code and platform configurations, including automation supporting monitoring platforms and platform operations.
- Well-rounded experience in infrastructure across hardware platforms, operating systems, networking, storage, and databases (MS SQL Server, Oracle, Cassandra), including common deployment patterns, integration architectures, scaling and resiliency considerations, and performance assessment.
- Experience implementing Infrastructure-as-Code (IaC) and configuration management practices using tools such as Terraform, enabling standardized provisioning and scalable, repeatable deployments.
- Hands-on experience operating in hybrid infrastructure environments, including enterprise on-prem platforms and public/private cloud, with familiarity supporting and migrating monitoring capabilities across cloud boundaries.
- Demonstrated ability to improve monitoring signal quality through baselining, threshold strategy, noise reduction, enrichment, and topology/context alignment, supporting reliable event-to-incident workflows and operational insights.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
Preferred qualifications, capabilities, and skills
- Hands on experience operating one or more enterprise monitoring platforms such as SCOM, Tivoli, SMARTS, IBM Instana, DX NetOps, ITNM ,Netcool Suite
- Experience with modern observability ecosystems such as Dynatrace, Grafana, Prometheus and interoperability patterns for telemetry integration, routing and visualization.
- Experience with Kubernetes (e.g., EKS) for container orchestration and operations.
- Experience with topology-driven monitoring and correlation approaches for large-scale infrastructure environments.
- Knowledge of Event Management & AIOps workflows (noise reduction, anomaly detection, probable cause analysis, guided remediation) with appropriate controls.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
Similar Jobs
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Designs, simulates, and optimizes digital, analog, and DRAM memory circuits for advanced HBM products. Responsibilities include CMOS circuit design, floorplanning, layout leadership, simulation using FINESIM, HSPICE, and Verilog, tape-out validation, silicon correlation, documentation, and cross-functional technical leadership across engineering, manufacturing, test, and marketing teams.
Top Skills:
Analog Circuit DesignCadence VirtuosoCmosDigital Circuit DesignDramFinesimHbmHspiceVerilogVlsi
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead tapeout execution and release coordination for HBM designs, manage schedules, ensure compliance with release prerequisites, and track closure of signoff items before tapeout.
Top Skills:
Hbm DesignsRcdbRelease CoordinationTapeout ExecutionToastTwit
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Research emerging AI workloads and computing architectures, evaluate memory and storage requirements, and analyze performance, power, cost, bandwidth, capacity, latency, and scalability tradeoffs. Develop simulations, benchmarks, models, and analytical tools for next-generation memory and storage concepts. Characterize workloads across CPUs, GPUs, accelerators, and memory-centric platforms while collaborating with architects and engineers on technology assessments and proof-of-concept evaluations.
Top Skills:
Ai AcceleratorsCachingCpusDramGpusHigh-Performance ComputingJaxMemory HierarchiesPythonPyTorchTensorFlow
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
