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Salary
$101k – $230k per year (Estimated)
Location
In office (Tel Aviv)
Seniority
Senior · 6+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Vega provides a Security Analytics Mesh (SAM) platform that enables full SecOps visibility with unified search, AI-powered detection, and accelerated response across all data sources without migration or ingestion.

Description

Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world's largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we're looking for people who want to be a part of the next rocket-ship in cyber.

We're looking for a Security Researcher to join our team at the intersection of security research, AI, and product. This isn't a traditional research role - you'll be deeply embedded in how the platform is built, working side by side with R&D, Product, and AI teams to make sure security expertise is baked into every layer of what we ship. You'll own detection and analytics research across cloud, identity, endpoint, and beyond, while actively shaping how AI capabilities are applied to solve real security problems at scale.

WHAT YOU WILL DO

  • Research and develop sophisticated detections and behavioral analytics across multiple security landscapes - cloud, identity, endpoint, network, and application - with a focus on coverage that scales across customer environments.
  • Work closely with R&D, Product, and AI teams as the security authority - reviewing features, shaping designs, and ensuring security logic is sound, practical, and impactful.
  • Apply an AI-native approach to detection and analytics challenges - leveraging LLMs, ML signals, and AI-assisted workflows to do things that rule-based approaches can't.
  • Identify gaps in detection coverage and analytical capabilities, and drive those findings directly into the product roadmap.
  • Analyze real-world attacker techniques and translate them into detection logic, hunting content, and analytical frameworks that ship as part of the platform.
  • Evaluate detection quality rigorously - measuring fidelity, coverage, and performance against real attacker behavior and production telemetry.
  • Stay sharp on the evolving threat landscape and rapidly incorporate new techniques, campaigns, and attacker tooling into our detection library.
  • Contribute to external research output - blog posts, talks, open-source tooling - that reflects our depth and point of view in the security community.

Requirements

WHAT YOU WILL BRING

  • 6+ years of hands-on experience in detection engineering, security research or incident response - working with real production data at scale.
  • Deep knowledge of attacker techniques and behavior across at least 2 from: cloud, identity, endpoint, and network environments, with the ability to translate that directly into high-fidelity detection logic.
  • An AI-native mindset - you've built or applied AI-powered tooling in a security context (detection pipelines, alert investigation, hunting workflows) and you default to AI-powered approaches before reaching for manual ones.
  • Experience working within or alongside a product or engineering team - you understand how software gets built, and you know how to make your security expertise actionable for R&D and Product.
  • Strong coding skills (Python or similar), used for research, data analysis, detection development, and tooling.
  • A product-oriented approach to research - you think about scale, usability, and customer impact, not just technical correctness.
  • Self-directed and a strong self-learner - you don't wait to be pointed at problems, and you move fast when you find them.
  • Strong written and verbal communication skills in English, with the ability to explain complex security concepts clearly to both technical and non-technical audiences.
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