Backend Engineer (Junior)
Neutron · Singapore River, Central Region ·
- Work mode
- Onsite
- Seniority
- Junior
- Employment
- Contract
- Category
- Backend
- Experience
- 5+ years
- Salary
- SGD 5,500 – 6,000 / month
Neutron · Singapore River, Central Region ·
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Junior Backend Engineer developing AI model capabilities and agentic workflows for cybersecurity, including vulnerability assessment and remediation. Key tech includes LLMs, AI orchestration, cloud AI services, and containerization for both cloud and air-gapped environments.
Salary: $5,500 – $6,000 per month
About the role
Develop and adapt AI model capabilities for cybersecurity use cases, including security assessment automation, tool orchestration, vulnerability analysis, remediation planning, and controlled deployment into both cloud-based and air-gapped environments.
Key responsibilities
Develop and optimise AI model capabilities for cybersecurity use cases.
Build agentic workflows for AI-assisted vulnerability assessment, remediation recommendation, validation, and secure code fixes.
Orchestrate AI-powered cloud security testing and integrate findings into the security assessment platform.
Integrate AI capabilities with approved cybersecurity tools, scan outputs, and reporting workflows.
Establish guardrails, approval gates, and evaluation methods to ensure reliable, secure, and controlled AI-generated outputs.
Benchmark AI model and workflow performance across cloud and air-gapped environments.
About you
1–5+ years of experience in AI Engineering, or related fields.
Experience in AI/ML/Agentic frameworks, AI orchestration, LLMs, modal adaptation, model-serving, or fine-tuning.
Good understanding of cybersecurity workflows, vulnerability management, application security, and security automation.
Familiarity with cloud AI services, GPU-based model deployment, containerisation, and secure deployment practices.
Ability to evaluate model performance using defined benchmarks, datasets, and operational use cases.
Able to evaluate AI performance using data and benchmarks.
Able to iterate quickly and adjust approach when solutions do not meet requirements.
Comfortable building AI capabilities for controlled, offline, and air-gapped environments.
Strong awareness of AI safety, guardrails, governance, and handover requirements.
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