远程工作雷达

软件工程师 II - 全栈

Software Engineer II - Full Stack

开发工程限定地区(需当地身份)
公司abnormalsecurity
薪资未公开
工作地点Remote - USA
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-06-30
数据来源Greenhouse
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注意地域限制:该职位明确限定在 Remote - USA 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

职位描述

在 Abnormal AI,我们的使命是保护全球最大的企业免受高级电子邮件和协作攻击。威胁叙述团队将检测系统中的复杂信号转化为清晰、可操作的故事,帮助客户理解我们阻止的攻击以及我们平台的价值。

作为威胁叙述团队的全栈软件工程师,你将帮助构建跨邮件详情和威胁叙述视图的下一代以电子邮件为中心的叙述体验,重点是向客户清晰传达 Abnormal 的检测结果。你将与生成式 AI 和基于大语言模型的系统紧密合作,将数千个低级检测特征和信号提炼成简洁、可信的解释,使客户能够立即采取行动。你将从后端 API 和数据契约到客户门户和内部工具中高性能、直观的 UI,端到端地实现全栈功能。你的工作将直接影响客户对 Abnormal 检测质量的认知,以及他们如何大规模分析威胁。这个职位适合一位喜欢负责明确范围系统的工程师,能够从资深合作伙伴那里学习,并将扎实的工程基础与产品直觉和叙事能力相结合。

你将负责的工作包括:

  • 在资深工程师的指导下,设计并实现跨威胁叙述和邮件详情界面的全栈功能,包括客户门户组件、内部分析师工具和 QBR 面向的输出。
  • 实现并演进从攻击数据、增强信号和生成式 AI/大语言模型代理生成丰富叙述的 API 和服务,遵循已建立的合约和模式。
  • 为数据模型和可解释性合约做出贡献,使复杂的威胁决策更易于客户和内部分析师理解。
  • 编写高质量、经过充分测试的 Python/Django 和 React/Typescript 代码,注重正确性、性能和可维护性。
  • 通过在你负责的领域内构建和改进仪表盘、警报和操作手册,参与威胁叙述和邮件详情服务的 SLA/SLO、可观测性和事件响应的管理。
  • 与产品、客户成功、市场推广、威胁情报、检测和数据科学合作伙伴密切协作,确保叙述体验能清晰传达攻击背景、价值和客户成果。
  • 参与设计和代码评审,向更资深的工程师学习
查看英文原文

About the Role

At Abnormal AI, our mission is to protect the world’s largest enterprises from advanced email and collaboration attacks. The Threat Narrative team transforms complex signals from our detection systems into clear, actionable stories that help customers understand the attacks we stop and the value of our platform.

As a Software Engineer, Fullstack on the Threat Narrative team, you will help build the next generation of email-centric narrative experiences across Email Details and Threat Narrative views, with a focus on clearly communicating Abnormal detections to customers. You will work closely with GenAI and LLM-powered systems that distill thousands of low-level detection features and signals into concise, trustworthy explanations that customers can immediately act on. You will implement fullstack features end-to-end, from backend APIs and data contracts through to performant, intuitive UIs in the customer portal and internal tools that surface these explanations in the right context. Your work will directly shape how customers perceive Abnormal’s detection quality and how they reason about threats at scale. This role is ideal for an engineer who enjoys owning well-scoped systems, learning from senior partners, and combining strong engineering fundamentals with product intuition and storytelling.

What you will do

  • Design and implement fullstack features across Threat Narrative and Email Details surfaces, including customer portal components, internal analyst tools, and QBR-facing outputs, with guidance from senior engineers.
  • Implement and evolve APIs and services that generate enriched narratives from attack data, enrichment signals, and GenAI/LLM agents, following established contracts and patterns.
  • Contribute to data models and explainability contracts that make complex threat decisions more understandable to customers and internal analysts.
  • Write high-quality, well-tested Python/Django and React/Typescript code, focusing on correctness, performance, and maintainability.
  • Participate in owning SLAs/SLOs, observability, and incident response for Threat Narrative and Email Details services by building and improving dashboards, alerts, and runbooks in the areas you own.
  • Collaborate closely with Product, CS, GTM, Threat Intel, Detection, and DS partners to ensure narrative experiences clearly communicate attack context, value, and outcomes for customers.
  • Engage in design and code reviews, learn from more senior engineers, and surface opportunities to simplify, derisk, and improve existing systems.

Must Haves

  • 2+ years of professional, production-level software engineering experience, with a track record of shipping and operating fullstack web applications in cloud-native environments.
  • Proficiency in Python and Django (or a similar backend framework), and comfort working with Postgres or similar relational databases.
  • Experience building modern frontend applications with React and Typescript, including data-heavy or workflow-centric UIs.
  • Ability to design and work with well-structured APIs and data models for data-intensive applications, with attention to correctness and evolvability.
  • Experience using metrics, logging, and tracing to debug production issues and understand user behavior in at least one prior system.
  • Strong collaboration and communication skills, including working effectively with Product and partner engineering teams to translate requirements into clear technical tasks.
  • Experience with AI development tools.
  • Bachelor’s degree in Computer Science, Information Systems, or a related technical field, or equivalent practical experience.

Nice to Have

  • Experience building or integrating LLM/GenAI-powered features (e.g., prompt design, simple agents, or explainability) in production or pre-production systems.
  • Familiarity with cybersecurity data, threat intelligence, or detection systems, especially in the context of email and collaboration security.
  • Exposure to big data and batch processing technologies (e.g., Spark, Databricks, Airflow, Kafka) used to power analytics, narratives, or offline enrichment.
  • Experience collaborating on multi-team initiatives and contributing to shared components, data contracts, or cross-surface UX.

#LI-ML1

Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.
In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.

Base salary range:
$149,200—$214,500 USD

A note on AI in our process: 
Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.

Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

本页面信息整理自 Greenhouse,版权归原发布方所有。职位可能随时关闭,投递请以原始页面为准。 本站只做信息聚合展示,不参与招聘流程,也不向求职者收取任何费用。

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