Site Reliability Engineer III

JPMorganChase•Jersey City, NJ

30d

About The Position

There’s nothing more exciting than being at the center of a rapidly growing field in technology and applying your skillsets to drive innovation and modernize the world's most complex and mission-critical systems. As a Software Engineer III (Associate) at JPMorganChase within Employee Platform — Collaboration and Communication, you will be a seasoned member of an agile team designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. You will deliver critical technology solutions across multiple technical areas and business functions in support of firm objectives.

Requirements

Formal training or certification on software engineering concepts and 3+ years applied experience.
Hands-on experience across system design, application development, testing, and production/operational stability.
Strong coding skills in Linux, Bash, and Python
Proven ability to develop, debug, and maintain enterprise-scale code, including database querying; solid understanding of SDLC and end-to-end delivery.
Practical experience with Agile ways of working, including CI/CD, application resiliency, and security practices; exposure to modern technical domains such as cloud, AI/ML, and/or mobile, and their supporting technical processes.
Excellent communication and stakeholder management, adapting messages for senior business and junior technologists.
Pragmatic mindset to drive technical re-engineering/modernization while continuing business delivery.
Deep expertise in SRE best practices: reliability, scalability, performance, security, enterprise architecture, and toil reduction; able to promote SRE culture within the team.
Strong operational tooling knowledge: file transfers, SSL/certificates, load balancers, job scheduling, monitoring, backup/capacity, plus containers/orchestration (Docker/ECS/Kubernetes), CI/CD tools (Jenkins/GitLab/Terraform), and network troubleshooting; experience with enterprise-authorized AI-assisted dev tools and responsible AI use (validation, security, data sensitivity).
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

Nice To Haves

SIP / VoIP familiarity

Responsibilities

Deliver end-to-end software solutions (design, development, troubleshooting) with strong problem decomposition and innovative thinking beyond routine approaches.
Build and maintain secure, high-quality production code, including synchronous integrations and algorithm maintenance.
Produce architecture/design artifacts for complex applications and ensure implementation adheres to design constraints.
Analyze large, diverse datasets to create insights, visualizations, and reporting that drive continuous improvement.
Proactively identify hidden issues/patterns and use them to improve coding hygiene, reliability, and system architecture.
Champion site reliability culture: define, educate, and operationalize SLOs/SLIs/error budgets with product, engineering, and stakeholders; monitor and review regularly.
Drive delivery excellence through self-learning, issue/blocker resolution, and robust change & release management practices.
Apply knowledge of tools within the SDLC toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Lead cross-team operational responsibilities including hosting platform/infrastructure planning, data center migrations, partner engagements, audits/application hygiene, and contribute to engineering communities, knowledge sharing, and an inclusive, resilient team culture.
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.