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vinova pte. ltd.

Toa Payoh / Global

Software Quality Engineer

Job Description

Company Overview

Established in 2010, Vinova is an award-winning development company specializing in mobile, web, and enterprise applications. We serve global clients across IoT, blockchain, fintech, banking, networking, and ecommerce, delivering quality, flexible, and fast solutions.

Job Summary

You will apply your expertise in software engineering and cybersecurity to evaluate AI systems, interpret security and privacy requirements, and assess system designs to ensure safe and trustworthy AI applications.

Responsibilities

Apply 3+ years of experience in software engineering, cybersecurity, application security, AI assurance, SDET, or technical QA automation to secure AI and software systems

Analyze security and safety risks affecting large language models (LLM), retrieval-augmented generation (RAG), and agentic applications to mitigate vulnerabilities

Operate AI evaluation, red-teaming, benchmarking, or adversarial-testing tools such as Moonshot or Litmus to identify and address security gaps

Interpret and apply security, privacy, and AI governance requirements to ensure compliance and risk mitigation

Review system designs and data flows to assess trust boundaries and integration risks, enhancing system security posture

Develop and maintain Python scripts and tools to support security testing and automation efforts

Utilize AWS services, containerized environments, SQL databases, and implement access controls, logging, encryption, data classification, masking, retention, and secure handling of sensitive information to protect data integrity and confidentiality

Preferred competencies and qualifications

Conduct AI red-team exercises, AI threat modeling, or AI security and application assurance reviews to proactively identify AI-specific risks

Apply knowledge of AI and application security frameworks such as OWASP GenAI Security Project, NIST AI Risk Management Framework, or MITRE ATLAS to guide security practices

Test RAG pipelines, model integrations, agent tools, sandboxes, role-based access control (RBAC), tenant-isolation controls, and other AI-specific attack surfaces to strengthen defenses

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