You'll work as a senior individual contributor with real influence over architecture and product direction, collaborating directly with security researchers, data scientists, and product managers across our Poland and Israel teams (1-hour time difference – genuine daily collaboration, not satellite work).
What You'll Do
Own solutions end to end – from studying the domain and generating your own ideas, through research and design, to coding, shipping, and supporting them in production.
Drive independent research in a new domain where problems are not fully defined, balancing innovation with practical, cost-effective engineering
Build and evolve backend & frontend, extending traditional microservices with AI/LLM-based capabilities
Use AI agents throughout development – research, design, coding, and testing – to raise both speed and quality
Work closely with security researchers, data scientists, and product managers to turn ideas into shipped product
What We're Looking For
10+ years of backend software engineering experience, including 3+ years in a hands-on technical leadership role (Principal / Tech Lead / Architect)
A product mindset: you connect technical decisions to business impact
A team player with excellent communication skills, whos not afraid to touch every aspect of modern software product development (e.g. quality, documentation, customer-facing technical discussions)
Proven experience designing and building systems from scratch in a product environment – including reliable, concurrent, thread-safe services
Strong hands-on skills in a modern backend language (Go or Python preferred) and the ability to pick up new languages and technologies quickly
Real, hands-on experience using AI coding agents across the development lifecycle – you know their strengths, their failure modes, and how to guide them to high-quality results
Solid grounding in cloud environments and modern development practices (AWS, GCP, or Azure)
Nice to Have
Familiarity with AI security challenges (prompt injection, model leakage, adversarial attacks)
Experience integrating AI/LLM capabilities into real-world production systems – beyond out-of-the-box API calls (tuning, customization, evaluation)
Experience with ML workflows (training, deployment, inference) or tools such as LangChain, Hugging Face, or provider SDKs
Background in application security, cloud security, or DevSecOps
