As a Site Reliability Engineer III at JPMorgan Chase within the Commercial Investment Banking team of Fraud Prevention, you will solve complex and broad business problems with simple and straightforward solutions. Through code and cloud infrastructure, you will configure, maintain, monitor, and optimize applications and their associated infrastructure to independently decompose and iteratively improve on existing solutions. You are a significant contributor to your team by sharing your knowledge of end-to-end operations, availability, reliability, and scalability of your application or platform.
You are an integral part of a team that works to develop high-quality architecture solutions for various software applications and platform products. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains. You will ensure the platform is reliable, secure, performant, and resilient in production across Kubernetes-based environments and AWS. You will apply SRE principles to drive measurable improvements in availability and latency, reduce operational toil through automation, and strengthen deployment safety and recovery capabilities in close partnership with engineering and platform teams.
Job responsibilities
- Production ownership & reliability outcomes: Own day-to-day operational health for the platform, focusing on availability, latency, throughput, and error rates; proactively identify reliability risks and drive remediation.
- SLO/SLI and alerting strategy: Define and evolve SLIs/SLOs and error budgets; build actionable alerting aligned to customer impact and reduce noise through tuning and standardization.
- Observability & troubleshooting: Improve end-to-end observability (metrics, logs, traces), dashboards, and runbooks across Kubernetes and AWS; perform deep technical triage of distributed system issues.
- Incident response & problem management: Participate in on-call and lead/assist incident triage, mitigation, and recovery; conduct RCAs and drive corrective/preventive actions to closure.
- Kubernetes operations: Support containerized workloads, autoscaling, rollout/rollback procedures, resource tuning, and resilience patterns.
- AWS operations (container + serverless): Operate components on AWS (EKS/ECS/Lambda) and associated data services (Dynamo DB, S3); manage operational concerns such as scaling, retries, and safe failure modes.
- Release engineering & delivery reliability: Improve the safety and repeatability of deployments using Spinnaker and Harness.
- Infrastructure as Code & environment consistency: Build and maintain Terraform modules and automation for reliable, repeatable environments.
- Database reliability: Partner with engineering and database/platform teams to improve reliability patterns across multiple database technologies.
- Security & controls in operations: Apply secure operational practices and ensure operational processes meet required controls.
- Lead small-to-medium initiatives from proposal through production adoption.
- Uses enterprise-authorized AI capabilities within the work environment to accelerate incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
- Applies enterprise-authorized AI capabilities within the work environment to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse-first improvements tied to SLO outcomes.
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Experience in SRE/DevOps/production engineering or equivalent
- Hands-on experience operating Kubernetes workloads (deployments, scaling, debugging)
- Practical experience with AWS (EKS, ECS, Lambda, Dynamo DB, S3) in production
- Experience with CI/CD and release tooling such as Spinnaker and/or Harness
- Proficiency with Terraform (IaC), plus scripting/automation (Python/Bash/Go)
- Strong incident response skills, RCA writing, and ability to drive remediation work
- Solid fundamentals in Linux, networking, and troubleshooting distributed systems
- Ability to independently execute well-scoped reliability work and escalate when needed
- Working knowledge of using enterprise-authorized AI capabilities within the work environment to support SRE workflows with strong validation habits and awareness of data sensitivity
- Ability to validate AI-assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements
- Experience implementing SLO programs and alerting aligned to customer journeys
- Experience with performance testing, capacity planning, and resilience testing (fault injection/chaos, DR exercises)
- Experience improving operational maturity: standardized runbooks, automated health checks, auto-remediation, and deployment guardrails
- Experience with fraud screening/decisioning or payment flows
- Familiarity with database reliability patterns (capacity, backups, failover readiness)
- Experience with secure operational practices (least privilege, secrets handling)
- Experience partnering with engineering and platform teams to drive reliability improvements