Data Engineer

AI Data Engineer - AI AppSec | Cybersecurity

Location: Tel Aviv (Hybrid)

About the Company:

On behalf of our client, we're searching for a AI Data Engineer to join one of the standout cybersecurity startups in the market - a business that's moving fast, winning deals, and showing no signs of slowing down.

Funded multiple times over in rapid succession, our client has built an AI-powered platform that finds real, exploitable vulnerabilities on a continuous basis - giving enterprises a step-change advantage over attackers. The product is resonating, the logos are growing, and now they're building out the sales team to accelerate what's already working.

About the role:

As an AI Data Engineer, you'll build the intelligence infrastructure that sits at the heart of our client's AI-driven security platform. This isn't a traditional data role - you'll be engineering the memory and context that enables AI agents to think, retrieve, and act with precision, bridging the gap between large-scale data architecture and the fast-moving world of agentic AI. If you're a builder who's equally at home in data science, data engineering, and full-stack development, and you thrive in the space where all three overlap, this role was built for you.

Responsibilities:

• Design and manage end-to-end data pipelines that ingest, clean, and organise unstructured data from fragmented sources into high-performance vector databases
• Build context engineering pipelines that feed our AI agents with the right data at the right moment, reducing hallucinations and maximising reasoning quality
• Design and monitor agentic flows, performing deep trace analysis to understand how data processing impacts model performance
• Contribute across the stack - building APIs that expose data to models while keeping the underlying infrastructure robust, scalable, and secure
• Use AI-assisted tooling to accelerate development, optimise queries, and maintain a fast-delivery culture

Requirements:

• Proven experience building end-to-end applications in Node.js, Python, or Go, with hands-on cloud infrastructure management
• Strong expertise in ETL/ELT, data lake architectures (ex; Delta Lake), and real-time processing (ex; Kafka)
• Familiarity with vector databases (ex; Pinecone), orchestration frameworks (ex; LangChain), and trace analysis tooling
• Solid understanding of LLMs, embedding models, and how data quality directly influences RAG performance

Reach out to [email protected] if interested!