Lead Site Reliability Engineer, Operations Excellence for AI Platforms

JPMorgan Chase

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 39 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $182k

$134k $235k

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This listing doesn't post a salary. Most similar roles pay $146,837–$216,250.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Site Reliability Engineer, Operations Excellence for AI Platforms

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As a Lead Site Reliability Engineer - Operations Excellence for AI Platforms, you will join the AI Machine Learning and Data platform team to lead resiliency design reviews and mentor other engineers. You will design and implement solutions to enhance the reliability, scalability, and performance of AI/ML platforms while developing observability, security, automation, and fin-ops tools. Your daily work involves debugging production issues, participating in on-call rotations, and architecting distributed systems using AWS and cloud-native architecture. You must demonstrate expertise in Python, Infrastructure as Code, and Terraform. A core component of this role involves using enterprise-authorized AI capabilities to accelerate incident triage, troubleshooting, and post-incident analysis. You will also lead the adoption of AI-assisted reliability workflows across the software development life cycle to ensure traceability and security.

Skills

SRE Python Terraform AWS Kubernetes Infrastructure as Code CI/CD AI ML Distributed Systems Cloud-native Architecture Observability Automation fin-ops Incident Management Data Engineering

What you'll do

Design and implement solutions to enhance the reliability and scalability of AI/ML platforms.
Develop observability, security, automation, and FinOps tools and orchestration.
Define and evaluate standards and architecture for reliability and automation frameworks.
Debug production issues, identify root causes, and perform remediation.
Participate in on-call rotations, incident management, and escalation workflows.
Use enterprise-authorized AI to accelerate incident triage, troubleshooting, and post-incident analysis.
Lead the adoption of AI-assisted reliability workflows across the software development life cycle.
Mentor and guide junior engineers on technical and business issues.

What we're looking for

Formal training or certification on site reliability engineering concepts and 5+ years of applied experience.
Expertise in SRE principles, reliability, scalability, and performance of applications and infrastructure.
Expertise in programming with Python and Infrastructure as Code tools such as Terraform.
Experience architecting distributed systems and cloud-native architecture in AWS.
Experience using enterprise-authorized AI capabilities to improve SRE workflows with strong validation habits and data sensitivity awareness.
Ability to evaluate AI-assisted operational recommendations for correctness, risk, and security guardrails.
Systematic problem-solving skills and excellent communication skills to present technical concepts to stakeholders.
Prior experience in AI, ML, or Data engineering (preferred).
Expertise in container orchestration/Kubernetes (preferred).
Prior experience developing Automation frameworks/AI Ops or building observability and telemetry tools (preferred).
Previous experience as an SRE in a dynamic technology company or startup (preferred).

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