Elevate your engineering prowess to unprecedented levels by joining a team of exceptionally gifted professionals and position yourself among the top echelon in site reliability.
As an Associate Site Reliability Engineer at JPMorgan Chase within the Consumer & Community Banking Data and Analytics team, you will help build a meaningful engineering discipline, combining software and systems to develop creative engineering solutions to operations problems. Much of our support and software development focuses on optimizing existing systems, building infrastructure and reducing work through automation. You’ll join a team of curious problem solvers with a diverse set of perspectives who are thinking big and taking risks. In this environment you’ll take the lead on relevant projects, supported by an organization that provides the support and mentorship you need to learn and grow. As an SRE you’ll be focused on running better production applications and systems. You work with your fellow stakeholders to define non-functional requirements (NFRs) and availability targets for the services in your application and product lines. You will ensure those NFRs are accounted for in your products’ design and test phases, that your service level indicators are effectively measuring customer experience, and that service level objectives are defined with stakeholders and implemented in production.
Our Consumer & Community Banking Group depends on innovators like you to serve nearly 66 million consumers and over 4 million small businesses, municipalities and non-profits. You’ll support the delivery of award-winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers.
When you work at JPMorgan Chase & Co., you’re not just working at a global financial institution. You’re an integral part of one of the world’s biggest tech companies. In 14 technology hubs worldwide, our team of 40,000+ technologists design, build and deploy everything from enterprise technology initiatives to big data and mobile solutions, as well as innovations in electronic payments, cybersecurity, machine learning, and cloud development. Our $9.5B+ annual investment in technology enables us to hire people to create innovative solutions that will not only transform the financial services industry, but also change the world.
At JPMorgan Chase & Co. we value the unique skills of every employee, and we’re building a technology organization that thrives on diversity. We encourage professional growth and career development and offer competitive benefits and compensation. If you’re looking to build your career as part of a global technology team tackling big challenges that impact the lives of people and companies all around the world, we want to meet you.
Job responsibilities
- Collaborate with engineering teams to define, validate, and enforce Non-Functional Requirements (NFRs) including performance, scalability, availability, latency, and disaster recovery — for applications and data platforms, ensuring they meet production readiness standards before go-live.
- Conduct Failure Mode and Effects Analysis (FMEA) for critical services and platforms to systematically identify potential failure points, assess risk impact, and drive mitigation strategies. Contribute to Production Readiness Reviews (PRRs) to validate that services meet reliability, observability, and operability standards before onboarding into SRE support.
- Define, implement, and manage Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Error Budgets for services in your remit. Use error budget policies to drive data-informed conversations between reliability and feature velocity, escalating when burn rates indicate risk to customer experience.
- Implement and maintain infrastructure-as-code, CI/CD pipelines, and automated deployment strategies to ensure safe, consistent, and repeatable releases. Participate in change management processes to assess deployment risk and minimize blast radius during rollouts.
- Drive observability maturity across services through white and black box monitoring, structured logging, distributed tracing, and intelligent alerting. Develop and maintain dashboards, runbooks, and operational playbooks to ensure rapid incident detection, triage, and resolution.
- Participate in on-call rotations and lead incident response for production issues. Conduct blameless postmortems and Root Cause Analysis (RCA) for incidents, ensuring action items are tracked to closure. Contribute to Chaos Engineering initiatives and Game Day exercises to proactively validate system resilience and failure recovery mechanisms.
- Support SRE practices for AI/ML platforms and products by contributing to reliability, capacity planning, and incident response for AI/ML infrastructure components such as Databricks, Vector Databases, Model Serving endpoints, and ML pipelines. Leverage Agentic AI concepts and tools — including AI Agents, RAG, and automation frameworks — to assist in SRE functions such as intelligent incident triage, alert enrichment, runbook automation, and self-healing workflows.
- Measure, track, and reduce operational toil through automation of repetitive tasks, self-healing infrastructure patterns, and performance tuning. Collaborate with technical experts, stakeholders, and cross-functional teams to troubleshoot complex problems, while championing the adoption of site reliability engineering culture and best practices within the team.
Required qualifications, capabilities, and skills
- 8+ years of software engineering experience with 3+ years of applied Site Reliability Engineering experience in Data Warehousing, Oracle/Snowflake, SQL/PLSQL, and handling large data movement in public/private cloud environments. Proficiency in Python/Java for large-scale data movement and automation.
- Exposure to or hands-on experience in supporting SRE practices for AI/ML platforms and products, with familiarity in infrastructure components such as Databricks, Vector Databases, Model Serving endpoints, and ML training/deployment pipelines.
- Understanding of how to apply SRE fundamentals — including monitoring, incident response, capacity awareness, and toil identification — to AI/ML and data-intensive workloads, with the ability to define and track relevant SLOs/SLIs (e.g., model latency, inference availability, data freshness).
- Familiarity with Agentic AI concepts such as AI Agents, Skills, Context Management, and Retrieval-Augmented Generation (RAG), with the ability to leverage these tools to support SRE functions like incident triage, alert enrichment, runbook automation, and root cause analysis.
- Experience in observability including white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
- Experience with platforms and applications hosted on public/private/hybrid cloud environments, including container orchestration technologies such as Kubernetes, ECS, and Docker.
- Experience with continuous integration and continuous delivery tools such as Jenkins, GitLab, or Terraform.
- Familiarity with troubleshooting common networking technologies and issues.
- Ability to contribute to large, collaborative teams by presenting information logically and clearly, with limited supervision. Ability to initiate and implement ideas to solve business problems.
Preferred Qualifications
- Experience supporting reliability practices for AI/ML platforms, including model serving endpoints and ML pipelines.
- Experience with Databricks, vector databases, or large-scale feature or embedding pipelines in production environments.
- Experience applying automation techniques to reduce toil, including self-healing workflows and runbook automation.
- Experience with Kubernetes and containerized workloads in production. Proficient in site reliability culture and principles with familiarity in implementing site reliability practices within an application or platform. Formal training or certification in SRE concepts is preferred.
- Familiarity with distributed tracing practices for complex, multi-service systems.
- Experience running chaos engineering or game day resilience exercises.
- Familiarity with agentic AI concepts (for example, retrieval-augmented generation) to assist incident triage and operational workflows.