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Generative Ai Testing Jobs in Riverside, NJ (NOW HIRING)

Damco Solutions

GenAI Architect

Mount Laurel, NJ · On-site

... transformers; and generative AI architectures. • Experience with prompt engineering ... testing to validate model performance • Deploy models using cloud platforms (Azure) and MLOps ...

The Campbell's Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

This co-op / internship offers hands-on experience at the forefront of Generative AI and automation ... Key ResponsibilitiesPrototype AI Agents: Assist in building and testing AI agents designed to ...

The Campbell's Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentictechnologies. * Mentorship from senior AI Engineers ...

The Campbell's Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

This co-op / internship offers hands-on experience at the forefront of Generative AI and automation ... Key ResponsibilitiesPrototype AI Agents: Assist in building and testing AI agents designed to ...

The Campbell's Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

This co-op / internship offers hands-on experience at the forefront of Generative AI and automation ... Key ResponsibilitiesPrototype AI Agents: Assist in building and testing AI agents designed to ...

Law School Admission Council

Software Engineer

Newtown, PA · On-site

$108K - $115K/yr

... testing, and debugging, following team prompting standards and code-review practices for AI-generated code. * Contribute to the design and development of Generative AI features, such as chat ...

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How much do generative ai testing jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for generative ai testing in Riverside, NJ is $54.26, according to ZipRecruiter salary data. Most workers in this role earn between $44.66 and $62.16 per hour, depending on experience, location, and employer.

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Riverside, NJ?

For Generative Ai Testing jobs in Riverside, NJ, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Riverside, NJ look for?

The top searched job categories for Generative Ai Testing jobs in Riverside, NJ are:

What cities near Riverside, NJ are hiring for Generative Ai Testing jobs?

Cities near Riverside, NJ with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you

Senior Application Penetration Tester

Philadelphia, PA • On-site

Chubb
Insurance Services • 10K+ employees
Learn more about Chubbexternal

Full-time

Posted 17 days ago

Chubb rating

8.2

Company rating: 8.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

148th of 315 rated insurance

Job description


  • 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

Qualifications
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

About Us
Chubb is a world leader in insurance. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance, and life insurance to a diverse group of clients. The company is distinguished by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength, underwriting excellence, superior claims handling expertise and local operations globally.
At Chubb, we are committed to equal employment opportunity and compliance with all laws and regulations pertaining to it. Our policy is to provide employment, training, compensation, promotion, and other conditions or opportunities of employment, without regard to race, color, religious creed, sex, gender, gender identity, gender expression, sexual orientation, marital status, national origin, ancestry, mental and physical disability, medical condition, genetic information, military and veteran status, age, and pregnancy or any other characteristic protected by law. Performance and qualifications are the only basis upon which we hire, assign, promote, compensate, develop and retain employees. Chubb prohibits all unlawful discrimination, harassment and retaliation against any individual who reports discrimination or harassment.

What Chubb employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Chubb

Sourced by ZipRecruiter

Chubb is the world's largest publicly traded property and casualty insurer. With operations in 54 countries, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. We are a unique global organization with a culture of individuals passionately committed to our respective crafts. With underwriting at our core, each of us contributes to providing the best insurance coverage and service to our clients. Our highly collaborative, inclusive nature helps us drive better business outcomes through diversity of background, experiences, insights and values.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Warren, NJ, US

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