20 days ago
Singapore, SingaporeMid Level
Responsibilities
- Design and execute security and safety assessments for LLM, RAG, and agentic applications.
- Implement and operationalize Moonshot and Litmus testing, including test suites, adversarial scenarios, result analysis, and assurance evidence.
- Develop representative and synthetic test data while enforcing classification, masking, anonymization, retention, and disposal requirements.
- Translate security, privacy, government, and AI governance requirements into technical controls, test plans, risk assessments, and assurance evidence.
- Review AI solution architectures, data flows, trust boundaries, access controls, tenant isolation, logging, retention, model or service selection, and third-party integration risks.
- Document vulnerabilities and control gaps, guide remediation, validate fixes, communicate residual risk, and report assurance metrics and trends.
- Integrate automated AI security and evaluation tests into CI/CD pipelines, release processes, security regression checks, release gates, and acceptance criteria.
- Build and maintain automated functional, regression, API, and end-to-end tests using suitable frameworks.
- Investigate defects by reproducing issues, tracing application and cloud logs, isolating root causes, and reporting actionable findings.
- Promote reusable test assets and shared ownership of quality across product and engineering teams.
Requirements
- 3+ years of relevant experience in software engineering, cybersecurity, application security, AI assurance, SDET, or technical QA automation.
- Practical understanding of LLM, RAG, and agentic application security and safety risks.
- Hands-on experience with Moonshot, Litmus, or comparable AI evaluation, red-teaming, benchmarking, or adversarial-testing tools.
- Ability to interpret security, privacy, and AI governance requirements and translate them into controls, test plans, risk assessments, and assurance evidence.
- Experience reviewing system designs and data flows, assessing trust boundaries and integration risks, and recommending secure cloud architectures.
- Strong communication and facilitation skills for explaining technical risks and guiding stakeholders toward secure implementation decisions.
- Proficiency in Python and working knowledge of TypeScript or JavaScript, with automated API, functional, regression, or end-to-end testing experience.
- Familiarity with AWS services, containerized environments, SQL databases, access controls, logging, encryption, data classification, masking, retention, and secure handling of sensitive information.
- Preferred experience includes AI red-team exercises, AI threat modeling, AI security reviews, RAG pipeline testing, model integrations, agent tools, sandboxes, RBAC, and tenant-isolation controls.
- Preferred familiarity with the OWASP GenAI Security Project, NIST AI Risk Management Framework, MITRE ATLAS, government enterprise environments, and IM8.
Benefits
- Flexible work practices.
- 40 hours of self-development each year with a broad selection of learning opportunities.
- Opportunities to participate in community, charity, and volunteer initiatives.
- Diversity, inclusion, digital inclusion, and environmental sustainability programs.
Tech Stack
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.