Senior Lead Software Engineer - Java, AI

Salary: $61,000 - 101,000 per year Requirements:

• We expect formal training or certification in software engineering concepts, with 5+ years of hands-on experience developing, debugging, and maintaining code in a corporate environment using modern programming, scripting, and database querying languages such as Java, Python, Shell scripting, SQL, PostgreSQL, Oracle, SQL Server, or MySQL.
• We need 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 with platforms such as Jenkins, GitHub Actions, GitLab CI/CD, Bitbucket Pipelines, Harness, Argo CD, Artifactory, or Nexus.
• We require strong practical experience with Java, Spring Boot, Kafka, API development, Python, and Shell scripting for building automation services, test harnesses, evaluation tooling, pipeline instrumentation, and operational tooling using frameworks and tools such as REST APIs, OpenAPI/Swagger, Maven, Gradle, JUnit, Mockito, Selenium, Playwright, Cucumber, pytest, or SonarQube.
• We expect hands-on use of enterprise-authorized AI-assisted software development tools for coding, test creation, troubleshooting, or documentation, such as GitHub Copilot, Claude Code, enterprise-approved coding assistants, or internal AI agents, with the ability to critically assess, validate, and refine AI-generated output for correctness, performance, and security.
• We look for an understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, resiliency and security expectations, and the ability to coach peers on safe, effective usage with responsible AI controls, secure prompt and input-handling practices, AI output validation checklists, model-output review workflows, and audit evidence capture.
• We require hands-on experience with AWS or Azure cloud platforms, Kubernetes-based deployment automation, Docker, Helm, SQL databases, artifact repositories, secrets management, and controlled enterprise deployment environments using tools such as HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, container registries, blue/green deployment, canary releases, rollback automation, release gates, or environment promotion workflows.
• We expect comfort operating end-to-end on a subsystem under senior design direction, including implementation, deployment, observability, alert response, production support, runbook improvement, and ongoing refinement of quality and reliability signals using tools such as Prometheus, Grafana, Splunk, ELK/OpenSearch, OpenTelemetry, Datadog, or AppDynamics.
• We need a working understanding of Git internals, branching workflows, PR and merge tooling, repository governance, commit signing, and large-scale change orchestration using tools and controls such as Git, Bitbucket, GitHub, GitLab, branch protections, signed commits, PR approval workflows, Dependabot-style dependency scanning, Checkmarx, Snyk, Black Duck, or Fortify.
• We expect demonstrated experience leading effective use of approved AI-assisted software development tools, such as for coding, code review, test acceleration, or troubleshooting, with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• We require strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations, along with experience coaching engineers on safe, compliant adoption within delivery practices.
• Preferred: 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.
• Preferred: proficiency in Python, Java, or similar languages, with exposure to model-evaluation tooling or ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent platforms.
• Preferred: experience automating infrastructure-as-code development or remediation using AI/ML-assisted workflows, including Terraform, Ansible, CloudFormation, or equivalent enterprise IaC frameworks.
• Preferred: deep experience with observability automation and reliability analysis using Prometheus, Grafana, ELK/OpenSearch, OpenTelemetry, or equivalent enterprise monitoring platforms.
• Preferred: excellent problem-solving, communication, and collaboration skills, with experience partnering across engineering, security, platform, SRE, and application-owner teams.

• We design and integrate AI-driven remediation workflows into enterprise CI/CD pipelines, including trigger design, build and test gating, deployment readiness checks, failure handling, and evidence capture for downstream audit and operational review.
• We build and run the evaluation harness that proves agent quality and delivery readiness at scale, including tracking success rate, regression rate, PR-merge rate, pipeline pass rate, drift detection, and control effectiveness across runtime, framework, standards, and CVE-remediation skills.
• We implement the PR-provenance contract end to end under the Sr Leads design, including branch creation, CI/CD hook integration, build-verification gates, automated test evidence, audit-trail emission, signed commit and merge attestation, rollback envelope, and operational handoff for failed or blocked runs.
• We own key subsystems within the harness, including evaluation-fixture management, replay tooling, regression corpora, quality-signal aggregation, failure triage, runbook maintenance, and day-to-day operational support.
• We co-own reliability and observability for the agent harness, including metrics, logs, traces, replay tooling, alerting, dashboards, and failure-pattern analysis so agent behavior and pipeline outcomes are diagnosable at scale.
• We contribute to agent-skill design reviews as a second set of eyes on evaluation coverage and provenance implications, and we escalate audit-control questions to the L5.
• We support the Standards pillar and Tooling pillar by wiring broad rollout of new lint rules, template upgrades, quality gates, and migration checks into the evaluation harness and CI/CD flow so bulk agent runs can demonstrate standards adoption at Channels scope.
• We instrument value, adoption, and operational metrics for the evaluation and provenance subsystems, including the number of repositories evaluated, number of provenance-signed PRs, pipeline pass and failure rates, repeat-run reduction, engineering days saved, and audit-evidence completeness.
• We drive adoption of enterprise-authorized AI-assisted engineering practices within the team to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of effective patterns.
• We apply knowledge of tools within the software development life cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

• AI
• AI Agents
• API
• AWS
• OpenSearch
• Ansible
• Azure
• BitBucket
• CI/CD
• Claude Code
• Cloud
• Copilot
• Cucumber
• Datadog
• DevOps
• Docker
• ELK
• Flow
• Git
• GitHub
• GitLab
• Gradle
• Grafana
• Helm
• Support
• JUnit
• Java
• Jenkins
• Kafka
• Kubernetes
• Maven
• MySQL
• Nexus
• OpenAPI
• OpenTelemetry
• Oracle
• Playwright
• PostgreSQL
• Prometheus
• PyTorch
• Python
• REST
• SQL
• Security
• Selenium
• Splunk
• Spring
• Spring Boot
• Swagger
• TensorFlow
• Terraform
• pytest

More:

Hackajob is partnering with J.P. Morgan to connect exceptional professionals with this Lead Software Engineer opportunity within JPMorgan Chases Commercial & Investment Bank Digital Channel team. We build autonomous agent capabilities that can plan, execute, validate, and submit code changes in bulk, with a focus on safe scaling through evaluation harnesses, PR-provenance controls, CI/CD integrations, and operational readiness. JPMorganChase is one of the oldest financial institutions and provides innovative financial solutions to consumers, small businesses, and leading corporate, institutional, and government clients under the J.P. Morgan and Chase brands. We offer a competitive total rewards package, with base salary based on role, experience, skill set, and location, and eligible roles may include commission or discretionary incentive compensation. We also provide benefits and programs such as comprehensive health care coverage, on-site health and wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. We value diversity and inclusion and are an equal opportunity employer.

last updated 36 week of 2026