Job Description

We are looking for an engineer who can apply AI, data analysis, and automation to secure the software supply chain. This is not a “train a model” research role — it’s a practical, hands-on position where you’ll use LLMs, analytics, and automation to detect risks, prioritize fixes, and harden systems ranging from container images to package dependencies. You will turn messy vulnerability and SBOM data into clear, actionable security improvements.

Responsibilities:

• Build and optimize pipelines that use SBOMs, CVE data, and AI/ML to assess and harden software components.
• Apply AI/ML techniques to prioritize vulnerabilities, suggest fixes, and detect high-risk patterns across large dependency sets.
• Automate ingestion and normalization of advisories, scanner output, and vendor data for security decision-making.
• Experiment with LLMs to reduce manual triage, generate draft remediation guidance, and summarize vendor notices.
• Provide data-driven recommendations for securing containers, AMIs, ISOs, packages, and third-party dependencies.
• Develop dashboards and metrics (e.g., risk scores, patch coverage, remediation timelines) for engineering and leadership.
• Document workflows and enable other teams to use AI/automation in supply chain security.

Qualifications:

• DOD Clearance Eligibility.
• Proficiency with AI/ML or data science tools (Python, Pandas, or similar).
• Experience using LLMs for workflow automation, data analysis, or summarization.
• Solid understanding of software supply chain security concepts (containers, packages, SBOMs, vulnerability management).
• Hands-on with scanners and SBOM tools (Trivy, Grype, Syft, Anchore).
• Strong data wrangling skills — building scripts or automations to process vulnerability and SBOM datasets.
• Clear communication skills to explain AI-driven findings to engineering, security, and compliance audiences.

Nice to Have:

• Active Secret or Top Secret Clearance.
• Familiarity with supply chain security frameworks (SLSA, NIST 800-218, CIS Benchmarks).
• Exposure to compliance or vendor risk management.
• Experience with cloud-native security tooling (Docker Scout, Snyk, GUAC).
• Contributions to open source supply chain security or data automation projects.

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