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Tech Stack
Tools & technologiesAzureCloudCyber SecurityDjangoDockerFlaskMongoDBPostgresPython
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- Competitive benefits to support financial, physical and mental wellbeing
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Pythonbackend engineeringREST APIsFastAPIFlaskDjangoLLM APIsRAGprompt engineeringagent orchestration
Soft Skills
strong communication skillsfluency in English
