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DevOps Engineer WIth AI and ML

  • Source: LinkedIn
  • TALENDICA
  • On-site
  • New York City
  • Mid level

Job Description

Position: Senior Automation Engineer

Location: NYC, NY (3 days onsite is must in person is must)

Duration: 12 Months

related to vulnerability, security and application of AI for detection and remediation experience is required Experience with ML/Deep Learning

Role: Automation Engineer — AI-Driven Code Security & Remediation Framework

Role Summary

Builds and operates a system that scans GitHub/Artifactory repos for vulnerabilities and EOL libraries, then uses AI-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)
  • 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

Skills

  • Github
  • Python
  • jfrog
  • jfrog-artifactory
  • snyk
  • codeql
  • dependabot
  • trivy
  • semgrep
  • github-actions
  • Jenkins
  • Docker
  • Airflow
  • apache-airflow
  • JSON
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