Lead AI-Driven Automation Engineer (Java/Python)

Next Frontier Capital; Jersey City (NJ); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Software Engineer to build autonomous agent capabilities that plan, execute, validate, and submit code changes at scale. The role emphasizes evaluation harnesses, PR provenance, CI/CD integrations, and secure upgrade paths across runtime, framework migrations, and security remediation.

You will design AI-driven remediation workflows, operate the evaluation harness, and own subsystems while driving reliability, observability, and auditability in enterprise

Qualifications

• 5+ years of developing, debugging, and maintaining code in a corporate environment using Java, Python, Shell, and SQL databases.
• Experience contributing to CI/CD or release engineering platforms with automation and audit-trail tooling.
• Strong hands-on Java, Spring Boot, Kafka, API development and automation tooling.

Responsibilities

• Design and integrate AI-driven remediation workflows into enterprise CI/CD pipelines.
• Build and operate the evaluation harness to prove agent quality and delivery readiness at scale.
• Own subsystems within the harness including evaluation-fixture management and regression corpora.
• Co-own the agent harness's reliability, observability, and failure-pattern analysis.
• Contribute to agent-skill design reviews and audit-control questions.

Skills

Java

Python

Spring Boot

Kafka

API development

CI/CD

GitHub Actions

Docker

Kubernetes

OpenAPI/Swagger

Tools

Jenkins

Git

Maven

Gradle

Prometheus

Grafana

Job description

JPMorgan Chase is seeking a Lead Software Engineer to build autonomous agent capabilities that plan, execute, validate, and submit code changes at scale. The role emphasizes evaluation harnesses, PR provenance, CI/CD integrations, and secure upgrade paths across runtime, framework migrations, and security remediation.

You will design AI-driven remediation workflows, operate the evaluation harness, and own subsystems while driving reliability, observability, and auditability in enterprise