Senior Application Penetration Tester

Chubb•Philadelphia, PA

About The Position

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.

Requirements

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 Haves

Prior experience managing Information Security projects
Bachelor's Degree in Computer Science, Engineering, or other Engineering or Technical discipline, or equivalent relevant experience
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

Responsibilities

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