Senior AI-Powered AppSec Engineer

Edward Jones; Tempe (AZ); On-site; USD 140,000 - 170,000; Full time

Benefits offered by this job

401k retirement plan

Medical benefits

Paid holidays and vacation

Job summary

Edward Jones is seeking an experienced Application Security Engineer to operate an AI-enabled AppSec harness across the SDLC in Tempe, AZ. The role focuses on harness health, observability, and reliable findings to continuously improve secure software delivery for financial services.

You will collaborate with AppSec, DevSecOps, and platform teams, automate workflows with Python and CI/CD tooling, and ensure evidence quality and regulatory alignment, including NIST and FFIEC frameworks.

Qualifications

• Bachelor’s degree in Computer Science, Cybersecurity, Software Engineering, Information Technology, Engineering, or related field, or equivalent practical experience.
• 6+ years of experience in application security, secure software engineering, DevSecOps, platform engineering, security operations, or related cybersecurity engineering roles.
• Hands-on experience supporting security capabilities across CI/CD, source control, ticketing, artifact management, logging, and AppSec reporting workflows.
• Working knowledge of secure code review, vulnerability triage, exploitability analysis, remediation validation, threat modeling concepts, and secure SDLC practices.
• Practical experience with SAST, SCA, DAST, secrets scanning, API security testing, container security, IaC scanning, SBOMs, SARIF, and findings management.
• Experience with Jenkins, GitHub Actions, GitHub Enterprise, Jira/Azure DevOps, developer portals, observability platforms, and AppSec dashboards.

Responsibilities

• Operate and maintain the AI secure-code evaluation harness for source code repositories and SDLC.
• Monitor harness health across ingestion, orchestration, model routing, scanner integration, executions, evidence generation, remediations, and reporting.
• Build 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, GitHub Actions, GitHub Enterprise, Jira/Azure DevOps, AppSec 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 AppSec outcomes.

Skills

Application security

DevSecOps

Platform engineering

Security operations

SAST/SCA/DAST

CI/CD security

Python scripting

Education

Bachelor's degree or equivalent

Tools

Jenkins

GitHub Actions

GitHub Enterprise

Jira/Azure DevOps

AppSec dashboards

Observability platforms

Job description

Edward Jones is seeking an experienced Application Security Engineer to operate an AI-enabled AppSec harness across the SDLC in Tempe, AZ. The role focuses on harness health, observability, and reliable findings to continuously improve secure software delivery for financial services.

You will collaborate with AppSec, DevSecOps, and platform teams, automate workflows with Python and CI/CD tooling, and ensure evidence quality and regulatory alignment, including NIST and FFIEC frameworks.