Devsecops Engineer with Python

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) AI-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/AI remediation tools and evaluating fit before firm-wide adoption Skill Levels Expert Level resource: 8 to 10 or more total experience out of which at least three years of experience in the relevant AI driven automation for code scanning and remediation matching the above skills Advanced level: Total 6 8 years of total experience out of which at least three years of experience in the relevant AI driven automation for code scanning and remediation matching the above skills