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