AI Software Engineer (LLM, MCP, AI Agents) at StrangeBee

Job description

Join StrangeBee to build the future of AI-powered incident response. As an AI Software Engineer (LLM, MCP, AI Agents), you will be at the forefront of innovation, designing and deploying AI capabilities directly embedded into TheHive and Cortex.

Your mission is to transform how SOC analysts work by integrating advanced LLM-driven features, intelligent agents, and automation into mission-critical cybersecurity workflows. You will bridge cutting-edge AI research with production-grade software used by thousands of security professionals worldwide.

Responsibilities

AI solutions development

Design and build integrations between TheHive and Large Language Models (LLMs), embedding AI capabilities directly into analysts' workflows.

Design and implement AI agents to automate incident triage, observable enrichment, and customer feedback analysis.

Integrate LLM-powered features into TheHive and Cortex to enhance user experience and analyst productivity.

Contribute to the architecture of scalable, secure AI systems embedded within enterprise-grade products.

Innovation & production

Rapidly prototype and evaluate new AI use cases in cybersecurity (log analysis, pattern detection, report generation, knowledge assistance).

Deploy and maintain AI services and models in production environments (Docker, CI/CD, cloud infrastructure).

Ensure monitoring, observability, performance optimization, and cost control of AI systems.

Implement automated evaluation frameworks (LLM evals) to ensure reliability, quality, and continuous improvement.

Document your work and share knowledge internally to strengthen AI expertise across the company.

Success criteria (6 - 12 months)

AI integrations with TheHive are deployed, stable, and actively used by customers.

LLM-driven features significantly improve analyst efficiency and product experience.

A robust automated evaluation system ensures output quality and reliability.

You actively contribute to internal knowledge sharing (technical talks, documentation, best practices).

Requirements

AI & LLM expertise

Strong understanding of Large Language Models: architecture, training principles, fine-tuning, prompt engineering.

Experience building AI-powered applications in production.

Knowledge of Model Context Protocol (MCP) or ability to ramp up quickly.

Understanding of AI security risks (prompt injection, data leakage, model misuse).

Software engineering

Minimum 5 years of experience in software development.

Strong proficiency in Go (or equivalent such as Python, Rust, Java) with the ability to quickly contribute to Go-based systems.

Experience designing clean, maintainable, production-ready architectures.

Solid understanding of testing practices (unit, integration, end-to-end).

Infrastructure & DevOps

Strong experience with Docker and Docker Compose.

Experience with CI/CD pipelines (GitHub Actions or equivalent).

Familiarity with cloud environments (AWS or other providers).

Bonus

Interest in or experience with cybersecurity.

Experience with vector databases and Retrieval-Augmented Generation (RAG) systems.

Experience working on AI agent architectures.

Experience optimizing LLM performance, latency, and cost in production.

You might feel hesitant to apply if you don't match 100% of the requirements. This list is a guide. We encourage you to apply even if you are a partial match.

Hiring process

Discovery call with the hiring team (30 minutes).

Technical (AI) interview with the tech team (90 minutes).

Technical (Dev) interview with the tech team (1 hour).

Interview with the CTPO (30 minutes).

Interview with the Head of HR (30 minutes).