Vulnerability Management Engineering Intern 

What you'd do

• Operate and tune the scanning and assessment platforms covering infrastructure, endpoints, and cloud, and close gaps in asset coverage rather than assuming the inventory is complete.
• Build and maintain the pipelines that export, normalize, and store findings, reconciling asset identity and tagging across sources so that one host is not three records.
• Query and manipulate large security datasets to answer posture questions, and expand what they cover beyond CVEs toward misconfigurations, identity exposure, and other risk traditional scanning misses.
• Develop and refine the scoring logic that turns raw findings into a ranked, defensible work queue — exploitability, known exploited vulnerability status, threat intelligence, asset criticality, and exposure.
• Apply credit for compensating controls already deployed, and stay rigorous about the difference between a control that is merely present and one that genuinely interrupts the exploitation path.
• Assess whether a vulnerability is genuinely applicable and impactful in Copart's environment, and be comfortable reporting "this one does not matter here, and here is why." AI-Assisted Workflows & Automation
• Work fluently within AI-assisted and agentic workflows where language models perform enrichment, control assessment, and first-pass analysis at a scale no human could review by hand.
• Critically review AI-generated analysis before it influences a score, a report, or a remediation decision, taking full ownership of the output regardless of how it was produced.
• Build and maintain backend automation in Python or similar, with REST and GraphQL APIs and middleware, connecting security tooling to internal databases and platforms — including the agent skills and integrations the team relies on.
• Partner with Infrastructure teams (Network, Systems, DevOps, Endpoint Engineering) to embed patching and remediation into their existing workflows, so fixes are routed and tracked rather than chased.

What they want

• Demonstrable cybersecurity experience in vulnerability management, infrastructure or cloud security engineering, security operations, or security automation.
• Solid grasp of IT infrastructure fundamentals — operating systems, networking, DNS, system administration, cloud services, APIs — and the ability to reason about how a vulnerability is actually exploited.
• Hands-on scripting and automation ability in Python or a comparable language, with a working understanding of database structures (SQL or NoSQL) and data manipulation.
• Practical familiarity with AI-assisted engineering workflows, including LLM tooling used for analysis or automation, and the judgment to verify and correct what those tools produce. This is a core expectation of the role, not a bonus.
• Proven ability to judge a vulnerability's real applicability and impact in a large, dynamic enterprise rather than deferring to a vendor severity rating.
• Exceptional written and verbal communication, with clarity and audience-appropriate messaging — this is a non-negotiable attribute.
• Strong analytical skills, attention to detail, and the intellectual honesty to say "I do not know yet, and here is how I will find out." Preferred
• Approximately 2+ years in IT infrastructure (network, systems, or security administration) plus time in a dedicated cybersecurity engineering or operations role.
• Experience operating enterprise vulnerability scanning platforms, cloud security posture management tooling, and endpoint detection and response platforms.
• Experience with API architectures and middleware (REST, GraphQL, FastAPI), version control and pull request collaboration, and configuration management tooling such as Ansible.
• Experience building or extending AI agent tooling, custom skills, or tool-server integrations that connect language models to operational systems.