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Salary
≈ $109k – $211k per year (Estimated)
Location
In office (Philadelphia)
Seniority
Senior · 2+ years exp

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Aug 24, 2026. Chubb scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Chubb is the largest publicly traded property and casualty insurer in the world, formed in 2016 when ACE acquired the older Chubb Corporation and took its name. It writes commercial property and casualty, specialty lines, high net worth personal insurance, accident and health cover and reinsurance across more than fifty countries, and it is known in the industry for underwriting discipline and for walking away from business it considers underpriced. Headquartered in Zurich with major operations in New York and Philadelphia, it is listed on the New York Stock Exchange.
  • Plan and execute penetration tests across web, mobile (iOS & Android), API, cloud-native/containerized, and AI/LLM-integrated applications
  • Assess AI/ML and generative AI-powered features for risks such as prompt injection, insecure output handling, training data poisoning, model denial of service, and sensitive information disclosure, aligned to the OWASP Top 10 for LLM Applications and MITRE ATLAS
  • Partner with AI/ML engineering and data science teams to threat-model AI-powered features and embed security testing into MLOps and CI/CD pipelines
  • Evaluate cloud-native and containerized workloads (AWS, Azure, GCP, Docker, Kubernetes) and Infrastructure as Code for misconfigurations and weak security controls
  • Test modern API architectures (REST, GraphQL, gRPC), including OAuth2, OIDC, and JWT authentication and authorization flaws, and microservices-based applications
  • Conduct mobile application security testing and reverse engineering, including hardcoded credentials, insecure keychain storage, and anti-emulator/obfuscation bypass
  • Own the overall vulnerability remediation status of the global application portfolio, and serve as the primary point of contact for application teams on remediation matters
  • Manage application risk rating processes and ensure timely risk scoring of new and changing applications
  • Build and maintain dashboards and status reports for portfolio leads and CIOs, and follow up on overdue vulnerabilities to meet compliance timelines
  • Develop clear, actionable penetration test reports and communicate findings and remediation strategy to both technical and executive stakeholders
  • Research emerging attack techniques and tooling, and drive automation and process improvements across the testing program

Minimum:

  • Prior experience managing Information Security projects
  • Bachelor's Degree in Computer Science, Engineering, or other Engineering or Technical discipline, or equivalent relevant experience
  • Minimum of 2 years' professional experience performing web application, API endpoint, and mobile (iOS & Android) penetration testing
  • Knowledge of prioritizing remediation activities with operational teams through risk ratings of vulnerabilities and assets
  • Knowledge of industry standards regarding vulnerability management, including Common Vulnerabilities and Exposures (CVE) and Common Vulnerability Scoring System (CVSS)
  • Knowledge of technology and security topics including network security, wireless security, application security, infrastructure hardening and security baselines, and web server and database security
  • Knowledge of penetration testing principles, tools, and techniques
  • Working experience with industry frameworks (OWASP, OWASP API Security Top 10, OWASP Top 10 for Large Language Model (LLM) Applications, NIST, NIST AI Risk Management Framework, MITRE ATT&CK, etc.)
  • Comfortable working outside their comfort zone with a willingness to learn
  • Excellent verbal and written communication skills
  • Strong analytical skills
  • Strong team player with the ability to work independently
  • Strong project management skills and ability to multi-task
  • Self-motivated with strong initiative
  • Knowledge of computer networking concepts and protocols, and application security methodologies
  • Skill in performing impact/risk assessments
  • Familiarity with modern application architectures, including cloud-native (AWS, Azure, GCP), containerized (Docker, Kubernetes), microservices, and API-first (REST, GraphQL, gRPC) designs
  • Foundational understanding of AI/ML and generative AI security risks (e.g., prompt injection, model manipulation, sensitive data leakage) is a plus

Nice To Have:

  • Strong understanding of secure SDLC, exploit/attack techniques, and core networking, application, and OS concepts, with the ability to manipulate application logic, bypass security controls, and develop exploits
  • Experience scoping and leading engagements end-to-end - from kickoff through remediation tracking - and improving testing efficiency through automation, tooling, and process improvements
  • Proficient with industry-standard tools across categories: Kali Linux, Metasploit, Nmap, Burp Suite/OWASP ZAP (web); Santoku, Genymotion, APKTool, JD-GUI (mobile); SQLMap, Semgrep, Snyk, Checkmarx/AppScan/Veracode (code); Postman/Insomnia (API); Trivy/Grype, Prowler/ScoutSuite (cloud & containers); and Garak/PyRIT (AI red-teaming)
  • Skilled in identifying OWASP Top 10 (Web & Mobile), OWASP API Security Top 10, and OWASP LLM Top 10 vulnerabilities, and developing secure coding checklists based on OWASP ASVS
  • Experience conducting full-scope assessments and penetration tests - web, mobile, API, social engineering, and server/client-side attacks - including mobile reverse engineering (hardcoded credentials, SQLi, keychain exposure, anti-emulator/obfuscation bypass)
  • Experience assessing cloud-native and containerized applications (AWS, Azure, GCP, Docker, Kubernetes), modern CI/CD pipelines and Infrastructure as Code, and modern API architectures (REST, GraphQL, gRPC) including OAuth2/OIDC/JWT flaws
  • Experience or working knowledge testing AI/ML and generative AI features for risks such as prompt injection, insecure output handling, training data poisoning, and sensitive data disclosure, aligned to the OWASP LLM Top 10 and MITRE ATLAS, plus working knowledge of securing AI agent/orchestration frameworks (LangChain, Semantic Kernel, AutoGen) and RAG vector databases
  • Skilled in code analysis, exploit development, and using attacker tools/tactics/procedures to identify, validate, and demonstrate vulnerabilities an adversary could exploit
  • Ability to analyze findings (including root cause analysis), risk-rate vulnerabilities by actual business impact, and prioritize key risk areas
  • Ability to document findings clearly, including reproduction steps, and produce comprehensive, accurate penetration test reports
  • Ability to research and recommend practical short- and long-term remediations, and communicate findings and strategy effectively to both technical and executive stakeholders
  • Experience working closely with development teams to track remediation through to production deployment, maintain vulnerability status dashboards, and follow up on overdue items to meet compliance timelines
  • Preferred certifications: OSCP, OSWE, GWAPT, GPEN, CEH, GCPN, CCSP, or equivalent AI/ML security credentials
  • Strong communicator and collaborative team player, able to adapt and reprioritize as project needs shift
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