Automation Engineer With AI Tools Exp-NYC,NY-Only Locals-F2F Interview

[David Miller]

Role: Al-Driven Code Security & Remediation Framework
NYC,NY-Only Locals-F2F Interview
Contract


Role Summary:
Builds and operates a system that scans GitHub/Artifactory repos for vulnerabilities and EOL
libraries, then uses Al-driven automation to remediate findings-cutting manual triage and patch
time firm-wide.  
Core Technical Skills:
● Programming: Strong Python (scanners, orchestration, API integration); basic Bash for
CI/CD glue
● Source & Artifact Systems: GitHub (Actions, Advanced Security, PR workflows) and
JFrog Artifactory/Xray; ability to scale across multi-repo, multi-language codebases
● Scanning Tools: Hands-on with Snyk, Xray, CodeQL / Dependabot. Trivy, or Semgrep:
understanding of CVE/CVSS scoring and EOL-detection sources (e.g., endoflife.date)
● Al-Driven Remediation: Building agentic workflows (LLM-based) that interpret findings,
generate patch PRs, run tests, and summarize fixes; prompt engineering for code-editing
agents
● CI/CD & Orchestration: Integrating scan-and-fix pipelines into GitHub Actions/Jenkins;
Docker for isolated fix-testing; scheduling via Airflow/cron
● Reporting: Structuring findings (JSON/SQL) into dashboards for tracking coverage and
trends
Supporting Skills:
● Security fundamentals (injection, auth flaws, supply-chain/SBOM risk)
● Risk-based prioritization beyond raw CVSS scores
● Semantic versioning awareness for safe auto-upgrades
● Testing discipline-regression validation before auto-merge
Communication Skills
● Translating vulnerability data into concise, risk-framed leadership updates (exposure
counts, MTTR, fix-rate trends)
● Writing clear status emails on scan coverage and outstanding critical items
● Building the business case (time saved, risk reduced) for non-technical stakeholders
● Continuous Learning
● Tracking emerging agentic/Al remediation tools and evaluating fit before firm-wide
adoption