AI Engineer (Junior)
Must-have:CloudAISecurity
Role Summary
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.
Key Requirements
- 3–5+ 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.
Preferred Attributes
- 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.