Design, build, and deploy production‑grade GenAI applications using LLM APIs
Own end‑to‑end feature delivery, including backend development in Python, API design, and UI integration
Implement RAG pipelines, agentic workflows, and tool‑calling in operational cybersecurity systems
Integrate AI workloads with log platforms, data lakes, automation workflows, and security tools
Build and maintain REST APIs (FastAPI) to support scalable AI services
Engage with cybersecurity stakeholders to refine requirements and demonstrate capabilities
Ensure reliability, scalability, and maintainability of deployed AI software solutions

Strong proficiency in Python and backend engineering for production systems
Hands‑on experience designing and building REST APIs (FastAPI, Flask, or Django)
Practical experience integrating LLM APIs (OpenAI, Claude, Gemini, etc.) and applying RAG, prompt engineering, and agent orchestration
Experience working in cloud environments (Azure preferred) and familiarity with DevOps tools
Strong communication skills and fluency in English.
Advantageous: Experience with PostgreSQL/MongoDB, Docker, CI/CD, Azure services, SOAR platforms, or cybersecurity operations (SOC, detection engineering, incident response). Frontend engineering experience is a plus

Cyber Security AI Engineer

Key skills