Staff Vulnerability Management Analyst- AI Automation Security Researcher

Vulnerability Discovery & Security Research (40%) Conduct deep-dive source code audits of UKG products (Java, .NET, Python, JavaScript) to discover novel vulnerabilities — examples could be hardcoded secrets, authentication bypasses, injection flaws, cryptographic weaknesses, access control gaps, unsafe deserialization, etc. Develop working proof‑of‑concept exploits that demonstrate real impact — not theoretical risk, but provable exploitation with clear data exposure or access escalation. Perform variant analysis: when you find a bug, systematically search the entire codebase for every instance of the same root‑cause pattern. Triage and validate findings from automated scanners (SAST, DAST, SCA) — separate real vulnerabilities from false positives using source‑level analysis. Investigate and reproduce externally reported vulnerabilities (bug bounty, CVEs, vendor advisories) to assess actual exploitability in UKG's environment. Collaborate with engineering teams on remediation — not just filing tickets, but working with developers to design, validate fixes, and drive to remediation. Build AI‑assisted vulnerability discovery tools using automation (Claude, MCP servers, custom models, etc.) for automated source code analysis, vulnerability pattern matching, and exploit generation. Develop autonomous security scanning agents that can analyze codebases, identify vulnerability patterns, and produce validated findings with minimal human intervention. Build automated vulnerability lifecycle pipelines: intake from scanners, AI‑assisted triage and deduplication, intelligent ticket routing, SLA tracking, and remediation verification. Contribute to the team's shared automation repositories and Claude Code skills store — every tool you build should be reusable by the rest of the team. Support vulnerability management program metrics and dashboards — contribute to reporting that gives leadership real‑time visibility into risk posture. Support compliance‑driven vulnerability management requirements, including FedRAMP continuous monitoring and POA&M processes, as UKG expands into federal markets. Publish internal/external research on novel vulnerability classes, AI‑assisted discovery techniques, and lessons learned from audits. Stay current on emerging vulnerability classes, exploitation techniques, and defensive patterns relevant to UKG's technology stack. Mentor other team members on vulnerability research methodology, source code analysis, and AI‑augmented security tooling. Qualifications 7+ years of hands‑on experience in vulnerability research, application security, or penetration testing — with a track record of finding real vulnerabilities in production software. Demonstrated ability to read and audit source code in at least two of: Java, C#/.NET, Python, JavaScript/TypeScript, Go, C/C++. Experience developing working proof‑of‑concept exploits — not just scanning, but understanding root causes and proving exploitability. Strong proficiency in Python for building security tools, automation pipelines, and integrations. Experience with AI/ML tools for security — using LLMs for code analysis, building AI‑assisted security tooling, or developing autonomous security agents. Deep understanding of common vulnerability classes: injection (SQL, command, LDAP), broken authentication, cryptographic failures, SSRF, deserialization, path traversal, access control, and their variants. Experience with vulnerability management programs — triaging, tracking, and driving remediation of vulnerabilities across engineering organizations. Ability to work directly with development teams — explaining vulnerabilities, reviewing proposed fixes, and validating remediations. Excellent written communication — ability to produce clear vulnerability reports, technical documentation, and executive summaries. Bachelor's degree in Computer Science, Cybersecurity, or equivalent experience. Published CVEs, security advisories, or bug bounty findings in production software. Experience in SaaS/multi‑tenant environments processing sensitive data (HCM, payroll, healthcare, financial). Familiarity with SAST/DAST/SCA tooling and how to reduce false positive rates through source‑level validation. Experience with cloud security assessment (AWS, GCP, Azure) including container and Kubernetes vulnerability analysis. Familiarity with FedRAMP, NIST SP 800‑53, or federal compliance frameworks — enough to understand vulnerability remediation timelines and reporting requirements in regulated environments. Security certifications that demonstrate hands‑on skill: OSCP, OSWE, GWAPT, GXPN, BSCP, or equivalent. Conference presentations, published research, or open‑source security tool contributions. Experience with reverse engineering, binary analysis, or firmware security. #J-18808-Ljbffr UKG