Site Reliability Engineer III

There's nothing more exciting than being at the center of a rapidly growing field in technology and applying your skills to drive innovation and modernize the world's most complex and mission-critical systems. At JPMorganChase, you'll have the opportunity to work on platforms that move money globally — where reliability, security, and performance are not just goals, they are requirements.

As a Site Reliability Engineer III at JPMorganChase within the Commercial & Investment Bank — Payments Technology team, you will solve complex and broad business problems with simple, straightforward solutions. Through code and cloud infrastructure, you will configure, maintain, monitor, and optimize highly available, low-latency payment processing platforms and their associated infrastructure. You are a significant contributor to your team, sharing your knowledge of end-to-end operations, availability, reliability, and scalability — and helping to raise the bar for the entire team.

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Job responsibilities

- Guide and assist teammates in building appropriate-level designs, gaining peer consensus, and supporting the adoption of site reliability engineering best practices across the team
- Collaborate with software engineers and cross-functional teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines
- Implement infrastructure, configuration, and network as code for payment processing applications and platforms, ensuring consistency, repeatability, and auditability
- Monitor and maintain Kafka-based data ingestion pipelines, supporting the reliability and throughput of high-availability, low-latency payment flows
- Collaborate with technical experts, key stakeholders, and team members to resolve complex problems and proactively address issues using service level indicators and objectives before they impact customers
- Implement and improve observability solutions — including OpenTelemetry, Grafana, Splunk, and Dynatrace — to drive transparency, faster incident response, and measurable service level objective outcomes
- Apply enterprise-authorized AI capabilities to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse-first improvements tied to service level objective outcomes
- Use enterprise-authorized AI capabilities to accelerate incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data in accordance with security and sensitivity requirements
- Proactively identify roadblocks and drive improvements to solve business problems, including exploring new technologies such as AI agentic models and MCP-based frameworks where appropriate

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Required qualifications, capabilities, and skills

- Formal training or certification on site reliability engineering concepts and 3+ years applied experience
- Proficiency in site reliability culture and principles, with familiarity in how to implement site reliability practices within an application or platform
- Proficiency in at least one programming language such as Python, Java/Spring Boot, or .NET
- Experience with observability practices such as white and black box monitoring, service level objective alerting, and telemetry collection
- Experience with continuous integration and continuous delivery tooling
- Proficient knowledge of software applications and technical processes within a given technical discipline such as cloud, AI, or distributed systems
- Familiarity with containers, container orchestration, and troubleshooting common networking technologies and issues
- Working knowledge of using enterprise-authorized AI capabilities to support site reliability engineering workflows, with strong validation habits and awareness of data sensitivity
- Ability to validate AI-assisted operational recommendations before applying changes, escalating when uncertain and adhering to data sensitivity requirements

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Preferred qualifications, capabilities, and skills

- Experience supporting highly available, secure, and low-latency payment processing platforms in a financial services environment, including familiarity with fraud screening or payment flow patterns
- Hands-on experience with Kafka and event-driven data ingestion pipelines, and working knowledge of AI agentic models and MCP-based frameworks applied to reliability use cases
- Proficiency with observability tooling such as OpenTelemetry, Grafana, Splunk, or Dynatrace, with a track record of improving reliability through monitoring, incident response, and automation
- Experience implementing service level objective programs, performance testing, capacity planning, and resilience testing including fault injection, chaos engineering, and disaster recovery exercises
- Experience improving operational maturity through standardized runbooks, automated health checks, auto-remediation, and deployment guardrails
- Familiarity with database reliability patterns including capacity management, backup strategies, and failover readiness, as well as secure operational practices such as least privilege and secrets handling