Software Engineer III - Performance and Resiliency Engineering

JP Morgan Chase; Chicago (IL); On-site; USD 114,000 - 155,000; Full time

Job summary

JPMorganChase in Chicago, IL, is seeking an experienced Software Engineer III to advance performance and resiliency engineering across mission‑critical platforms. You will design and deliver secure, scalable software while leading reliability initiatives and AI-assisted tooling adoption.

The role emphasizes distributed systems performance, cloud-native practices, and production readiness; responsibilities cover testing, monitoring, incident handling, and safe release strategies in a

Qualifications

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Experience improving performance and stability of high-volume platforms.
• Experience in performance engineering for distributed systems and SRE-style reliability engineering.
• Strong cloud/container background (AWS + Kubernetes/EKS, ECS).
• Experience with modern observability tooling.
• Experience leading use of AI-assisted development tools in engineering teams.
• Knowledge of responsible AI use and secure handling of data.
• Ability to tackle design and functionality problems independently.
• Practical cloud-native experience.

Responsibilities

• Contribute performance engineering efforts: load/stress/soak testing, capacity modeling, performance tuning, and regression prevention (KPIs, guardrails, and acceptance criteria).
• Improve production readiness: observability, actionable alerting, incident triage, and root-cause analysis leading to durable remediation.
• Apply resiliency patterns: timeouts/retries, circuit breakers, backpressure, graceful degradation, and failover readiness.
• Support safer releases via canary/progressive delivery and automated rollback patterns.
• Optimize containerized workloads across EKS (primary) and ECS/other compute; drive autoscaling and right-sizing.
• Develops secure and high-quality production code; reviews and debugs code written by others.
• Drives adoption of AI-assisted engineering practices, establishes validation standards, and promotes reuse of proven patterns in the SDLC/TLM toolchain.
• Applies SDLC tools and AI-assisted automation to improve value and performance.

Skills

Performance engineering

Cloud & containers

Observability

AI-assisted development

Reliability engineering

Tools

AWS

Kubernetes

EKS

ECS

Datadog

Grafana

OpenTelemetry

CloudWatch

Splunk

Prometheus

Job description

Software Engineer III - Performance and Resiliency Engineering

Chicago, IL, United States and 1 more

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Consumer & Community Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Schedule: Full time

Job Shift: Day

Base Pay/Salary: Chicago,IL $114,000.00-$155,000.00

Locations:

• 10 S Dearborn St, Chicago, IL, 60603, US
• 8181 Communications Pkwy Bldg F, Plano, TX, 75024, US

Job responsibilities

• Contribute performance engineering efforts: load/stress/soak testing, capacity modeling, performance tuning, and regression prevention (KPIs, guardrails, and acceptance criteria).
• Improve production readiness: observability (metrics/logs/traces/APM), actionable alerting, incident triage, and root-cause analysis leading to durable remediation.
• Apply resiliency patterns: timeouts/retries, circuit breakers, backpressure/rate limiting, graceful degradation, and failover readiness.
• Support safer releases via canary/progressive delivery and automated rollback patterns.
• Optimize containerized workloads across EKS (primary) and ECS/other compute where applicable; drive autoscaling strategy and right-sizing.
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Experience improving the performance and stability of critical, high-volume platforms.
• Experience in performance engineering for distributed systems and/or SRE-style reliability engineering in production.
• Strong cloud/container background (AWS + Kubernetes/EKS, ECS etc.).
• Experience with modern observability tooling (e.g., Splunk, Datadog, Dynatrace, Grafana, OpenTelemetry, CloudWatch or equivalent).
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience

Preferred qualifications, capabilities, and skills

• Hands-on with load/performance tools (JMeter, Gatling, k6) and JVM profiling.
• Experience with resiliency patterns and chaos/fault-injection testing.
• Proficient with observability tooling (Prometheus, Grafana, OpenTelemetry) for baselines and capacity planning.