Lead Software Engineer - Java or Python, Agentic AI

JPMorgan Chase & Co. • Jersey City, NJ

2d • $156,750 - $215,000

About The Position

As a Lead Software Engineer on JPMorgan Chase's Commercial & Investment Bank Digital Channel team, you will build autonomous agent capabilities that plan, execute, validate, and submit code changes in bulk. The role focuses on evaluation harnesses, PR-provenance controls, CI/CD integrations, and operational readiness to scale machine-authored changes safely across runtime upgrades, framework migrations, security remediation, and standards adoption.

You will design AI-driven remediation workflows, build and operate evaluation and provenance subsystems, and support the reliability, observability, rollout, and measurement of agent-enabled engineering workflows. Under senior design direction, you will own subsystems from implementation through deployment, production support, and continuous improvement, while helping teams use enterprise-authorized AI-assisted engineering practices safely and effectively.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience developing, debugging, and maintaining code in a corporate environment using modern programming, scripting, and database-query languages.
• Experience contributing to CI/CD, DevOps, or release-engineering platforms, including release pipelines, build and test automation, signed-attestation systems, deployment controls, or audit-trail tooling.
• Strong hands-on experience with Java, Spring Boot, Kafka, API development, Python, and Shell scripting for automation services, test harnesses, evaluation tooling, pipeline instrumentation, and operational tooling.
• Hands-on experience with enterprise-authorized AI-assisted software development tools for coding, testing, troubleshooting, or documentation, and ability to critically evaluate and refine generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure input and output handling, resiliency and security expectations, and ability to guide peers on safe usage and validation practices.
• Hands-on experience with AWS or Azure, Kubernetes-based deployment automation, Docker, Helm, SQL databases, artifact repositories, secrets management, and controlled enterprise deployment environments.
• Ability to operate a subsystem end-to-end under senior design direction, including implementation, deployment, observability, alert response, production support, runbook improvement, and iteration based on quality and reliability measures.
• Working understanding of Git internals, branching workflows, PR and merge tooling, repository governance, commit signing, and large-scale change orchestration.
• Demonstrated experience leading effective use of approved AI-assisted software development tools and setting team expectations for validating AI outputs for correctness, performance, and security.
• Experience coaching engineers on safe, compliant adoption of AI-assisted workflows, including secure handling of inputs and outputs and adherence to resiliency and security expectations.

Nice To Haves

• Formal training or certification in software engineering, AI/ML engineering, or cloud-native engineering, with experience applying agent-based systems or automation in enterprise delivery.
• Proficiency in Python, Java, or similar languages, with exposure to model-evaluation tooling or ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience automating infrastructure-as-code development or remediation using AI/ML-assisted workflows, including Terraform, Ansible, CloudFormation, or equivalent frameworks.
• Deep experience with observability automation and reliability analysis using Prometheus, Grafana, ELK/OpenSearch, OpenTelemetry, or equivalent platforms.
• Excellent problem-solving, communication, and collaboration skills, with experience partnering across engineering, security, platform, SRE, and application-owner teams.

Responsibilities

• Design and integrate AI-driven remediation workflows into enterprise CI/CD pipelines, including triggers, build and test gates, deployment-readiness checks, failure handling, and evidence capture for audit and operational review.
• Build and operate evaluation harnesses to measure agent quality and delivery readiness at scale, including success and regression rates, PR-merge and pipeline pass rates, drift detection, and control effectiveness.
• Implement the PR-provenance contract under the Sr Lead's design, including branch creation, CI/CD hooks, build-verification gates, automated test evidence, audit-trail emission, signed commit and merge attestation, rollback provisions, and operational handoff for failed or blocked runs.
• Own evaluation-harness subsystems such as fixture management, replay tooling, regression corpora, quality-signal aggregation, failure triage, runbook maintenance, and day-to-day operational support.
• Co-own reliability and observability for the agent harness, including metrics, logs, traces, replay tooling, alerting, dashboards, and failure-pattern analysis.
• Contribute to agent-skill design reviews, assessing evaluation coverage and provenance implications, and escalate audit-control questions to the L5.
• Support Standards and Tooling pillars by integrating new lint rules, template upgrades, quality gates, and migration checks into the evaluation harness and CI/CD flow.
• Instrument value, adoption, and operational metrics for evaluation and provenance subsystems, including repositories evaluated, provenance-signed PRs, pipeline outcomes, repeat-run reduction, engineering days saved, and audit-evidence completeness.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish consistent validation standards and promote reuse of effective patterns.
• Apply knowledge of the Software Development Life Cycle toolchain, including authorized AI-assisted development and automation capabilities, to improve the value realized from automation.

Benefits

• Competitive total rewards package, with base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed