Role overview
IONIX crawls, parses, and collects internet-scale data on assets, technologies, and vulnerabilities. As a data engineer, you'll work on top of this data - building the detection logic, enrichment processes, and AI-powered workflows that turn raw signals into accurate, actionable findings. You'll own detection quality end-to-end.
What you'll work on
- Agentic AI frameworks
- Web application security knowledge
- Databricks or similar data platform
- Internet research tools (Shodan, FOFA, BuiltWith)
- Own accuracy and coverage of detection capabilities such as: technology fingerprinting, SSO/login identification, vulnerability-to-technology mapping
- Build AI-powered workflows (LLM classifiers, automated rule generation) to scale detection beyond manual rule-writing
- Design eval frameworks and feedback loops - golden datasets, precision/recall tracking, regression testing - to keep quality high as automation grows
- Tune IP/domain discovery logic: decision rules, blacklists, thresholds, unstructured data parsing
- Extend BI pipelines and schemas to enrich asset data
- Investigate customer-reported detection gaps; root-cause and fix systematically
What we're looking for
- Python (scripting, automation, data analysis)
- Hands-on AI/LLM engineering - building multi-step pipelines with LLM APIs, not just prompting
- Evaluation mindset - experience measuring and maintaining accuracy of automated systems
- Regex, SQL, ETL concepts
- Web fundamentals (HTML, HTTP, JS) and basic networking (DNS, WHOIS, CIDR)
- Familiarity with CVE/CPE vulnerability ecosystem
- Git workflow
Tags & focus areas
Used for matching and alerts on DevFound Ai Data Science Data Engineer Generative Ai