AI-Powered SRE Lead for Autonomous Infrastructure

Testing Site - JPMC; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase is seeking a Senior Lead Site Reliability Engineer to define NFRs, set availability targets, and ensure SLIs/SLOs are met for AI-powered infrastructure. You will lead AI agent and MCP server initiatives, design robust observability pipelines, and guide teams across multiple data stores and platforms.

You will mentor engineers, champion SRE adoption, and collaborate on distributed systems, cloud-native tech, and CI/CD—driving enterprise-scale resilience and automation.

Qualifications

• Formal training or certification in software engineering concepts with 5+ years of applied experience in Site Reliability Engineering, DevOps, or Software Engineering
• Advanced knowledge in site reliability culture and principles with demonstrated ability to implement site reliability within an application or platform
• Advanced knowledge and experience in observability such as white and black box monitoring, service level objectives, alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
• Expert-level proficiency in Java, Go (Golang), Python, and Terraform for building enterprise-grade applications, high-performance systems, automation, and infrastructure as code
• Advanced knowledge of software applications and technical processes with considerable depth in multiple technical disciplines including distributed systems, microservices architecture, and cloud-native technologies
• Hands-on experience building AI Agents and autonomous systems with proficiency in AI frameworks (LangChain, LangGraph, AutoGen, CrewAI) and leveraging AI development tools (GitHub Copilot, Claude, etc.) to accelerate development and innovation
• Expertise in designing and implementing logging pipelines (Fluentd, Logstash, Vector) and systems for metrics collection, analysis, and distributed tracing
• Strong experience building production-grade RESTful APIs and designing message queue architectures (Kafka, RabbitMQ, SQS) for event-driven systems
• Experience with graph databases (Neo4j, TigerGraph), vector databases (Pinecone, Weaviate, Chroma), and integrating multiple data stores for AI-powered systems
• Proficiency with containerization (Docker, Kubernetes), CI/CD pipelines, and GitOps workflows
• Ability to communicate data-based solutions with complex reporting and visualization methods, recognized as an active contributor of the engineering community, and continues to expand network and leads evaluation sessions with vendors to see how offerings can fit into the firm's strategy

Responsibilities

• Creates high quality designs, roadmaps, and program charters for AI-powered automation systems, intelligent monitoring solutions, and next-generation reliability platforms that are delivered by you or the engineers under your guidance
• Provides advice and mentoring to other engineers and acts as a key resource for technologists seeking advice on technical and business-related issues, particularly in the intersection of SRE and AI/ML technologies
• Demonstrates site reliability principles and practices every day and champions the adoption of site reliability throughout your team
• Collaborates with others to create and implement observability and reliability designs for complex systems that are robust, stable, and do not incur additional toil or technical debt, including comprehensive logging pipelines and systems that export, analyze, and visualize observability metrics and traces across distributed systems
• Designs and builds AI Agents and MCP Servers for autonomous operations including incident detection, root cause analysis, and auto-remediation, while architecting solutions that integrate multiple data stores including graph databases, vector databases, transactional databases, analytical databases, and big data platforms
• Develops automation scripts and infrastructure-as-code using Java, Go, Python, and Terraform to improve operational efficiency, and builds and maintains RESTful services, APIs, and message queue architectures for event-driven systems and platform automation
• Makes significant contributions to JPMorgan Chase's site reliability community via internal forums, communities of practice, guilds, and conferences

Skills

SRE principles

Java

Go

Python

Terraform

AI/ML integration

Observability

Distributed systems

Cloud-native

Communication

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

Grafana

Dynatrace

Prometheus

Datadog

Splunk

Fluentd

Logstash

Vector

Kafka

RabbitMQ

Job description

JPMorgan Chase is seeking a Senior Lead Site Reliability Engineer to define NFRs, set availability targets, and ensure SLIs/SLOs are met for AI-powered infrastructure. You will lead AI agent and MCP server initiatives, design robust observability pipelines, and guide teams across multiple data stores and platforms.

You will mentor engineers, champion SRE adoption, and collaborate on distributed systems, cloud-native tech, and CI/CD—driving enterprise-scale resilience and automation.