Bulge Bracket Investment Banks

Posted 10 days ago

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**Site Reliability Engineer II - Tampa, FL** - Design and deliver reliability solutions, minimizing guidance for independent medium-scale projects. - Solve business problems with robust, maintainable code across payment processing and data ingestion workflows. - Maintain high-availability, low-latency payment platforms, troubleshoot incidents, and enhance observability (OpenTelemetry, Grafana). - Manage Kafka-based data pipelines, ensuring data integrity and resilience. - Eliminate toil and automate tasks, applying AI for incident management, with strong validation skills. - Bring 2+ years of SRE experience, cloud infrastructure management, and familiarity with AI-assisted operations. - Preferred: payment processing environment experience, Kafka proficiency, and secure, regulated technology familiarity.

Compensation: Not specified
City: Tampa
Country: United States

Full Job Description

Location: Tampa, FL, United States

Play a key role in ensuring the reliability, resilience, and performance of mission-critical payment processing platforms at one of the world's most iconic and largest financial institutions. In this role, you'll bring together software engineering discipline and operational expertise to help power the systems that move money globally reliably, securely, and at scale.

As a Site Reliability Engineer II at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you will use technology to solve complex business problems and apply software engineering best practices to improve system reliability. You will work independently on small to medium projects while collaborating with cross-functional teams to deepen your knowledge of payment platforms, observability tooling, and AI-assisted operations. This is an opportunity to grow your engineering skills in a high-impact, fast-paced environment where your contributions directly support the stability of global financial infrastructure.

Job responsibilities

Execute small to medium reliability projects independently, progressing toward designing and delivering solutions end-to-end with minimal direction

Write high-quality, maintainable, and robust code to solve business problems, following software engineering best practices across payment processing and data ingestion workflows

Support the reliability of high-availability, low-latency payment platforms by participating in incident triage, diagnosis, and resolution working with teams to address root causes, not just symptoms

Implement and improve observability solutions including service level indicators, service level objectives, and alerting using tools such as OpenTelemetry, Grafana, Splunk, and Dynatrace

Monitor and maintain Kafka-based data ingestion pipelines, ensuring data integrity, throughput, and resilience across payment processing flows

Identify and eliminate toil through systems engineering, automation, and application code improvements, with a focus on measurable reliability outcomes

Apply enterprise-authorized AI capabilities to accelerate incident triage, troubleshooting, post-incident analysis, and runbook drafting, while validating outputs and handling operational data in accordance with security and sensitivity requirements

Leverage AI agentic models and MCP-based frameworks to identify recurring reliability risks from operational signals, prioritizing improvements that drive measurable service level objective outcomes

Required qualifications, capabilities, and skills

Formal training or certification on site reliability engineering concepts and 2+ years applied experience

Ability to code in at least one programming language, with the ability to write automation scripts and contribute to reliability tooling

Experience maintaining cloud-based infrastructure, including deployment, scaling, and operational support

Familiarity with site reliability concepts, principles, and practices, including toil reduction and error budget management

Familiarity with observability practices such as white and black box monitoring, service level objective alerting, and telemetry collection

Familiarity with containers or a common server operating system such as Linux or Windows

Emerging knowledge of continuous integration and continuous delivery practices and related tooling

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 assess AI-assisted operational recommendations for correctness and risk, applying appropriate controls to maintain resiliency, security, and auditability

Preferred qualifications, capabilities, and skills

Hands-on experience supporting highly available, low-latency payment processing platforms in a financial services environment

Experience working with Kafka and event-driven data ingestion pipelines in production environments

Proficiency with observability tooling such as OpenTelemetry, Grafana, Splunk, or Dynatrace

Working knowledge of AI agentic models and MCP-based frameworks applied to operational or reliability use cases

Familiarity with secure, regulated technology environments and the controls required to maintain auditability and compliance

Play a key role in ensuring system reliability at one of the world's most iconic financial institutions.

Full Job Description