Senior SRE Engineer

Salary: $61,000 - 101,000 per year Requirements:

• We require formal training or certification in site reliability engineering, along with 5+ years of hands-on experience.
• We need advanced knowledge of SRE culture and principles, with proven ability to apply them in an application or platform environment.
• We look for deep experience in observability, including white-box and black-box monitoring, service level objectives, alerting, and telemetry using tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk.
• We expect expert-level proficiency in Java, Go, Python, and Terraform for enterprise application development, automation, and infrastructure as code.
• We require demonstrated experience using enterprise-authorized AI capabilities in the workplace to improve reliability engineering workflows, with strong validation habits and awareness of data sensitivity.
• We need the ability to establish safe AI usage practices for operations, including review and approval expectations and escalation paths, while maintaining resiliency, security, and auditability.
• We look for advanced knowledge of software applications and technical processes across distributed systems, microservices architecture, and cloud-native technologies.
• We require hands-on experience building AI agents and autonomous systems with frameworks such as LangChain, LangGraph, AutoGen, and CrewAI, plus familiarity with AI development tools like GitHub Copilot and Claude.
• We need expertise in designing logging pipelines and systems for metrics collection, analysis, and distributed tracing.
• We expect strong experience building production-grade RESTful APIs and message queue architectures such as Kafka, RabbitMQ, and SQS for event-driven systems.
• We require knowledge of graph databases, vector databases, and integrating multiple data stores for AI-powered systems.
• We need proficiency with containerization, CI/CD pipelines, and GitOps workflows.
• We look for the ability to communicate data-driven solutions through complex reporting and visualization methods, and to contribute actively within the engineering community.
• Preferred: experience with MCP servers or similar agent frameworks, including LLM integration, prompt engineering, and RAG.
• Preferred: familiarity with AI/ML model building, deployment, and lifecycle management using frameworks like TensorFlow, PyTorch, or scikit-learn.
• Preferred: experience with big data technologies, analytical databases, NoSQL databases, and time-series databases.
• Preferred: knowledge of security best practices and compliance in highly regulated industries, plus experience with chaos engineering tools and GameDay exercises.
• Preferred: contributions to open-source projects in SRE, observability, or AI/ML, and cloud certifications such as AWS, Azure, or GCP.
• Preferred: strong communication skills, with the ability to mentor others on site reliability practices and troubleshoot defects found during testing.

• We create and deliver high-quality designs, roadmaps, and program charters with the engineering team.
• We mentor technologists on technical and business matters, while serving as a culture carrier and champion for site reliability adoption.
• We collaborate to design and implement observability and reliability solutions for complex systems that are stable, robust, and avoid unnecessary toil or technical debt.
• We use enterprise-authorized AI capabilities to speed up reliability design and operational decision-making, including incident analysis and requirements traceability, while validating outputs and handling data according to sensitivity and security requirements.
• We drive the evolution and troubleshooting of critical components by understanding application and platform interdependencies and limitations.
• We provide ongoing guidance, tools, and solutions that support our firms growth.
• We contribute meaningfully to our site reliability community through internal forums, communities of practice, guilds, and conferences.
• We lead reuse-first adoption of AI-assisted reliability workflows across SDLC and toolchain practices, ensuring traceability, auditability, resiliency, and security controls.
• We collaborate with stakeholders to define non-functional requirements and availability targets, ensuring they are reflected in product design, testing, and production service-level objectives.

• AI
• AWS
• Azure
• Big Data
• CI/CD
• Cloud
• Copilot
• Datadog
• Dynatrace
• GCP
• GitHub
• GitOps
• Grafana
• Support
• Java
• Kafka
• LLM
• Marketing
• NoSQL
• Prometheus
• PyTorch
• Python
• RabbitMQ
• Security
• Splunk
• TensorFlow
• Terraform
• microservices
• Cassandra
• Docker
• Flink
• Golang
• Hadoop
• Kubernetes
• MongoDB
• Neo4J
• Network
• Spark

More:

We are JPMorganChase, one of the worlds oldest financial institutions, delivering innovative financial solutions to millions of consumers, small businesses, and major corporate, institutional, and government clients through the J.P. Morgan and Chase brands. Our history spans more than 200 years, and we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing, and asset management. We offer a competitive total rewards package with base salary based on role, experience, skill set, and location, and eligible roles may also receive commission-based pay or discretionary incentive compensation. Our benefits can include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. We are committed to diversity, inclusion, and equal opportunity, with reasonable accommodations available for religious practices, beliefs, and disability or mental health needs. This role sits within our Corporate Functions organization, supporting finance, risk, human resources, marketing, and other essential business areas.

last updated 36 week of 2026