Applied Cyber, Email Security (Detection Engineering)

Doppel is building an AI-native platform for social engineering defense across digital risk, human risk, and email security. The Applied Cyber, Email Security (Detection Engineering) role investigates email threats and detection failures, translating findings into detection logic, evaluations, AI behavior, and scalable product capabilities while partnering with Product, Engineering, customers, and go-to-market teams.

Responsibilities:

• Own detection problems end-to-end — from emerging TTP or FN → investigation → detection hypothesis → validation → production coverage → measurement
• Use AI as a force multiplier — build evals, supervise model behavior, use coding agents aggressively, and automate repetitive investigative work
• Partner with Product and Engineering on signals, detection logic, edge cases, and validation
• Work with customers and GTM on detection gaps, real-world TTPs, and platform behavior
• Turn tooling, threat-intelligence partnerships, and provider relationships into new signals and detection capabilities

Requirements:

• Bring deep practitioner judgment from one or more of detection engineering, SOC/IR, threat intelligence/OSINT, or email/messaging security; range across multiple areas is a major plus
• Take messy detection failures from “something's off” to root cause — prove what matters in the data and turn FP/FN cases into durable fixes
• Think like both attacker and defender across phishing, BEC, impersonation, credential theft, ATO, and evolving social-engineering TTPs
• Turn expert judgment into detection logic, evals, tests, requirements, and systems that scale beyond a single investigation or customer
• Thrive at the intersection of security, AI, product, and customers — challenge assumptions, use coding/AI agents aggressively, and move fast through ambiguity
• SEG/email-security depth: SPF, DKIM, DMARC, headers, mail flow, and sender identity
• Experience with M365/Exchange Online, Google Workspace, or email-security APIs
• Detection-as-code, eval datasets/labeling, model benchmarks, or LLM/ML security systems
• Built agentic security workflows, autonomous triage, or LLM evaluation systems
• Experience with Agentic SOC, SIEM/TI tooling, and threat-intelligence provider/vendor partnerships