DevOps - Lead Software Engineer

Testing Site - JPMC; Columbus (OH); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorgan Chase in Columbus, OH seeks a Lead Software Engineer to advance AI-powered observability and SRE maturity. You will ensure reliability, scalability and automation of AI-enabled applications and infrastructure, partnering with teams to deliver intelligent incident response and autonomic operations.

You will mentor engineers, shape the roadmap for AI-assisted SRE, and drive best practices across distributed systems, microservices and cloud architectures.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Demonstrates strong experience in SRE, DevOps, or Platform Engineering roles.
• Strong hands-on experience with AWS (ECS, Lambda, API Gateway, Bedrock, CloudWatch, RDS, EKS).
• Hands-on experience with AWS and LLM APIs.
• Expertise in observability tools: OpenTelemetry, Grafana, Prometheus, ELK, CloudWatch.
• Experience with CI/CD tools (GitHub Actions, Jenkins, Spinnaker ).
• Proven track record in automation, operational tooling, and event-driven workflows.
• In-depth understanding of distributed systems, microservices, and cloud architectures.

Responsibilities

• Ensure reliability, scalability, and performance of AI-assisted application and platform operations.
• Design and implement AI-driven solutions for intelligent alerting, noise reduction & auto-correlation systems.
• Build and maintain observability, monitoring, and telemetry for AI application and platforms.
• Build and support automation for alerting, anomaly detection, and self-healing workflows.
• Collaborate with engineering, and other stakeholders to drive operational excellence.
• Mentor and guide engineers on AIOps standards and operational excellence.
• Define and execute the roadmap for AI-assisted SRE and observability.

Skills

SRE

DevOps

Platform Engineering

AWS

Observability

CI/CD

Automation

Distributed Systems

Tools

Prometheus

Grafana

OpenTelemetry

ELK

CloudWatch

GitHub Actions

Jenkins

Spinnaker

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Enterprise Technology, you will be responsible for ensuring the reliability, scalability, and automation of AI-powered applications and infrastructure. In this role, you will be responsible for ensuring the reliability, scalability, and automation of AI-powered applications and infrastructure. You will partner with engineering, and other stakeholders to deliver modern observability, intelligent incident response, and autonomic operations across our applications.

Job responsibilities:

• Ensure reliability, scalability, and performance of AI-assisted application and platform operations.
• Design and implement AI-driven solutions for intelligent alerting, noise reduction & auto-correlation systems..
• Build and maintain observability, monitoring, and telemetry for AI application and platforms.
• Build and support automation for alerting, anomaly detection, and self-healing workflows.
• Collaborate with engineering, and other stakeholders to drive operational excellence.
• Mentor and guide engineers on AIOps standards and operational excellence.
• Define and execute the roadmap for AI-assisted SRE and observability.

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Demonstrates strong experience in SRE, DevOps, or Platform Engineering roles.
• Strong hands-on experience with AWS (ECS, Lambda, API Gateway, Bedrock, CloudWatch, RDS, EKS).
• Hands-on experience with AWS and LLM APIs.
• Expertise in observability tools: OpenTelemetry, Grafana, Prometheus, ELK, CloudWatch.
• Experience with CI/CD tools (GitHub Actions, Jenkins, Spinnaker ).
• Proven track record in automation, operational tooling, and event-driven workflows.
• In-depth understanding of distributed systems, microservices, and cloud architectures.

Preferred qualifications, capabilities, and skills:

• Experience with AI-powered coding assistants like GitHub Copilot, windsurf.
• Familiarity with prompt engineering, embeddings, and RAG pipelines.
• Experience building operational copilots or chatbots for runbooks or troubleshooting.
• Proficiency in Python