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Open nowPosted yesterday

AI Engineer – AI Safety and Cybersecurity

MyCareersFuture91,045 open roles

Pay
SGD 7,000 – SGD 9,000 a month
Where
Central, Singapore
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Your applicationOpen nowAI Engineer – AI Safety and CybersecurityMyCareersFuture · Central, Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on MyCareersFuture's own form.

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 1 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted yesterday

MyCareersFuture median: 1 days open

The posting

We are looking for an experienced AI Engineer to join our team and work on projects involving Agentic AI, AI safety, cybersecurity, vulnerability detection, and malware analysis.

The successful candidate will be involved in the design, development, evaluation, and implementation of AI-powered applications and agentic AI solutions for analysing software, detecting potential security vulnerabilities and malicious behaviours, and evaluating the safety and robustness of AI models.

Key Responsibilities

  • Design, develop, and implement AI-powered applications and Agentic AI solutions for real-world use cases.
  • Develop and enhance AI/LLM-based agents for software analysis, vulnerability detection, malware detection, and AI safety evaluation.
  • Design agentic workflows where AI agents can plan tasks, retrieve relevant context, use tools, reason over results, and generate structured outputs.
  • Develop AI-assisted solutions to analyse source code and identify potential software vulnerabilities and security issues.
  • Work with C/C++ source code, including large open-source software projects and Linux-based systems, for vulnerability analysis.
  • Integrate AI-based analysis with static analysis and other software security tools.
  • Analyse software packages and source code to identify potentially malicious or suspicious behaviours.
  • Support malware analysis of open-source software packages, including packages from ecosystems such as npm and PyPI.
  • Develop or enhance capabilities for detecting behaviours such as credential theft, data exfiltration, malicious downloads, remote payload execution, backdoors, and obfuscated code.
  • Support the evaluation of multimodal AI models, including image-text inputs, model responses, AI safety risks, attack methods, defence methods, and evaluation scores.
  • Prepare, process, and organise datasets and experimental results for AI model evaluation.
  • Develop scripts and tools to automate AI evaluation, security analysis, testing, and reporting.
  • Evaluate system performance using relevant AI, security, and system performance metrics.
  • Document experimental results, technical findings, system configurations, limitations, and implementation approaches.
  • Work closely with researchers, engineers, and project stakeholders to test, validate, and improve AI-based solutions.
  • Support deployment, integration, testing, documentation, and handover of developed solutions.

Technical Requirements

  • Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Cybersecurity, or a related discipline.
  • Minimum 5 years of relevant experience in software engineering, AI/ML engineering, application development, or a related technical field.
  • Hands-on experience developing and implementing software applications and/or Agentic AI applications in a production or real-world environment.
  • Strong programming skills in Python and experience developing end-to-end applications or AI solutions.
  • Hands-on knowledge of Machine Learning, Deep Learning, Large Language Models (LLMs), Generative AI, or Agentic AI.
  • Experience working with LLM APIs, AI agents, prompt engineering, tool/function calling, RAG, or agentic AI frameworks.
  • Strong understanding of software development fundamentals, including APIs, debugging, testing, version control, and working with source code repositories.
  • Familiarity with Git and Linux environments.
  • Understanding of cybersecurity concepts, software vulnerabilities, malware, or secure software development.
  • Ability to analyse complex technical problems, conduct experiments, and document findings clearly.
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