Software Engineer III - Performance and Resiliency Engineering

J.P. Morgan Chase & Co.; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

JP Morgan Chase is seeking a Software Engineer III to join the Consumer & Community Banking tech team. You will be a seasoned member of an agile team designing and delivering trusted, scalable technology products in a secure environment.

You will drive performance engineering for distributed systems, enhance production readiness with observability, and implement resiliency patterns while enabling safe, AI-assisted coding practices at scale. Strong cloud and container experience required.

Qualifications

• Formal training or certification on software engineering concepts with 5+ years of applied experience.
• Experience improving the performance and stability of critical, high-volume platforms.
• 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).
• Demonstrated experience leading effective use of AI-assisted software development tools with bounded validation of outputs.
• Strong understanding of responsible AI use in engineering workflows and security considerations.

Responsibilities

• Contribute performance engineering efforts: load/stress/soak testing, capacity modeling, performance tuning, and regression prevention.
• Improve production readiness: observability, alerting, incident triage, and root-cause analysis.
• Apply resiliency patterns: timeouts/retries, circuit breakers, backpressure, graceful degradation, and failover readiness.
• Support safer releases with canary/progressive delivery and automated rollback patterns.
• Optimize containerized workloads across EKS (primary) and ECS/other compute; drive autoscaling and right-sizing.
• Develop secure, high-quality production code, review and debug others' code.
• Drive adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish validation standards.
• Apply SDLC/TLM tooling knowledge to improve value realized by automation.

Skills

Performance engineering

Cloud/AWS

Kubernetes/EKS

Observability tooling

AI-assisted development

Secure coding

Resiliency patterns

Independent problem solving

OpenTelemetry

Tools

AWS

Kubernetes

EKS

ECS

Datadog

Splunk

Grafana

OpenTelemetry

CloudWatch

Job description

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 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 viacanary/progressive deliveryand automated rollback patterns.
• Optimize containerized workloads acrossEKS (primary)andECS/other computewhere 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.