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In office (Plano)
Seniority
Middle · 5+ years exp
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Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 4, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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 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.

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