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Application Security Engineer IV

Job in St. Louis, Saint Louis, St. Louis city, Missouri, 63105, USA
Listing for: Edward Jones
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    Cybersecurity, Information Security & Data Protection
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below
Location: St. Louis

This job posting is anticipated to remain open for 30 days, from 17-Aug-2026. The posting may close early due to the volume of applicants.

Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500¡ company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we’re proud to be privately-owned, placing the focus on our clients rather than shareholder returns.

Behind everything we do is our purpose:
We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging.

People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career.

View our Purpose, Inclusion and Citizenship Report.

¡Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating.

Team Overview:

The Application Security Engineer, Agentic Secure Code Harness Engineer is a hands-on role responsible for operating, monitoring, and improving an AI-enabled App Sec harness used to evaluate application and infrastructure source code for security vulnerabilities and insecure-design practices throughout the Secure SDLC lifecycle. The role focuses on harness health, observability, reliability, troubleshooting, evidence capture, and day-to-day operability of the App Sec process.

The engineer partners with App Sec, Dev Sec Ops , platform engineering, AI governance, and application teams to ensure reliability, accuracy of findings, and recommendations are actionable, evidence is repeatable, developer workflows remain aligned to the secure SDLC, AI model governance, and financial-services control expectations.

What You’ll Do:
  • Operate and maintain the AI secure-code evaluation harness for source code repositories, SDLC and lifecycle changes, and agentic security workflows.
  • Monitor harness health across ingestion, orchestration, model routing, scanner integration, executions, evidence generation, remediations, and reporting.
  • Build and tune observability dashboards and alerts for run success, queue depth, latency, cost management, model/API availability, regression failures, missing evidence, and integration outages.
  • Troubleshoot issues across development tooling such as:
    Jenkins, Git Hub Actions, Git Hub Enterprise, Atlassian, App Sec scanners, context tools, logging platforms, artifact repositories, and harness components.
  • Execute recurring operational routines, including run validation, readiness checks, benchmark refreshes, regression reviews, evidence-quality checks, and post-run reconciliation.
  • Maintain runbooks, SOPs, support playbooks, recovery steps, known-error documentation, and escalation paths.
  • Support secure ingestion and handling of source code, artifacts, scanner output, SBOMs, metadata, golden datasets, logs, and evidence packages.
  • Maintain benchmark suites, golden test cases, prompt/model configuration records, retrieval settings, scoring rubrics, and operational test data.
  • Validate that findings flow into developer workflows with context, severity, confidence, remediation guidance, traceability, and rejection rationale where applicable.
  • Collect audit-ready evidence aligned to NIST SSDF, NIST CSF 2.0, NYDFS, FINRA, SOX ITGC, FFIEC, GLBA, internal AI governance, and technology risk controls.
  • Report operational KPIs including run availability, failed-run rate, MTTR, validation cycle time, evidence completeness, cost per validated finding, false-positive trends, and developer remediation adoption.
  • Drive automation that reduces manual triage, improves repeatability, lowers operational toil, and increases developer trust in AI-assisted App Sec outcomes.
What Experience You’ll Need:
  • Bachelor’s degree in Computer Science, Cybersecurity, Software Engineering, Information Technology, Engineering, or related field, or equivalent practical experience.
  • 6+ years of experience in…
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