AI Engineer

Established in 2022, Guardz rapidly emerged as a noteworthy player in the cybersecurity sphere, securing $85M in funding and rallying a dedicated team of 100 industry professionals. Our vision is to foster a safer digital landscape for small and medium businesses across the globe. To this end, we introduced our comprehensive all-in-one Secure & Insure platform, and continue to grow and expand our team, our partnerships and our revenue.

We are seeking a talented and driven AI Engineer to join our innovative R&D team. In this role, you will focus on building cutting-edge AI solutions leveraging Large Language Models (LLMs) and modern agentic workflows, as well as developing backend systems and infrastructure to support our Generative AI initiatives.

The ideal candidate will have a strong foundation in machine learning, deep learning, and data analysis, coupled with expertise in exploratory data analysis (EDA), model evaluation, and performance optimization.

Responsibilities:

• Design, develop, and deploy state-of-the-art AI solutions into production.
• Build, optimize and evaluate end-to-end AI/ML pipelines for robust, scalable systems (including tooling / agentic workflows).
• Design and implement agentic systems (e.g., multi-step / multi-agent workflows) using modern frameworks (such as LangGraph, PydanticAI and Google Agent Developer Kit (ADK), etc.).
• Continuously research the latest advancements in AI and strategically integrate them into the product development lifecycle.
• Work collaboratively within the R&D team to ensure smooth integration of AI capabilities with existing and new product features.
  
  

• 5+ years of experience as a Machine Learning Engineer / Data Scientist / Software engineer or similar role, with a focus on production deployment.
• 1-2 years of hands-on experience working with LLMs (e.g., OpenAI GPT models, LLama, Gemini or other models).
• Experience building production-grade LLM applications (e.g., RAG systems, AI agents, copilots, or chat-based workflows).
• Solid background in software engineering, data science, or machine learning engineering.
• Proven ability to write and maintain production-level code in Python.
• Familiarity with agent AI architectures (planning, memory, tool orchestration) and standards such as MCP for tool and service integration is a strong plus.
• Strong soft skills: quick learner, proactive, self-driven, takes ownership, and thrives in fast-paced environments.
• Passion for AI, staying ahead of trends, and applying innovative solutions to real-world challenges.
  
  

• Cybersecurity domain knowledge.
• Experience with LLM application and agent frameworks (such as LangChain, PydanticAI, LangGraph, Google ADK, etc.) and AI orchestration platforms.
• Experience designing observability, evaluation, and monitoring for LLM agents (e.g., tracing, metrics, guardrails, offline/online evaluation).