Senior AI Automation Engineer

IMR Soft LLC; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

IMR Soft LLC is seeking a Senior AI Automation Engineer to design and operate an AI-driven remediation framework that scans GitHub and Artifactory repositories for vulnerabilities and outdated components. You will build agentic workflows using LLMs to interpret findings, generate patch PRs, run tests, and summarize fixes at scale across multi-language codebases.

The role emphasizes integrating scan-and-fix pipelines into GitHub Actions/Jenkins, containerized testing with Docker, and crafting

Qualifications

• Strong Python for scanners, orchestration, and API integration.
• Experience with GitHub Actions, Artifactory/Xray, and multi-repo codebases.
• Hands-on scanning with Snyk, CodeQL, Trivy, or Semgrep; understands CVE/CVSS and EOL sources.

Responsibilities

• Build and operate an AI-driven remediation system that scans repos for vulnerabilities.
• Interpret findings, generate patch PRs, run tests, and summarize fixes.
• Scale across multi-repo, multi-language codebases.
• Provide dashboards with findings and trends to leadership.

Skills

Python

CI/CD orchestration

Security basics

Testing discipline

Communication

Versioning awareness

Troubleshooting

AI remediation

Tools

GitHub Actions

JFrog Artifactory

Xray

Snyk

CodeQL

Dependabot

Trivy

Semgrep

Docker

Airflow

Jenkins

Job description

Position: Senior AI Automation Engineer

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

Duration: 12 Months

Role: Automation Engineer --- AI-Driven Code Security & Remediation Framework
focus to primary = 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

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