Job Description

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.

About IONIX

None

Responsibilities

• 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

Requirements

Required Skills

• 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

Nice to Have

• Agentic AI frameworks
• Web application security knowledge
• Databricks or similar data platform
• Internet research tools (Shodan, FOFA, BuiltWith)