Software Engineer – Backend – Behavioral Security Products

Emploi pas sur LinkedIn

🕒 il y a 7 jours

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🔙 Ingénieur Back-end

👻 Score fantôme 13%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Abnormal Security

Site WebLinkedInTous les Emplois

501 - 1000 employés

🔒 Cybersecurity

Cybersecurity

Abnormal offre une protection totale contre la plus large gamme d'attaques, y compris le phishing, les logiciels malveillants, le ransomware, l'ingénierie sociale, l'usurpation d'identité d'exécutifs, le compromis de la chaîne d'approvisionnement, le compromis de comptes internes, le spam et le graymail.

Description

• Design, build, and iterate on scalable backend and ML systems, APIs, frameworks, and internal tools • Own well-scoped features and components, with guidance from senior engineers on complex cross-system work • Contribute to the stability, reliability, and operational excellence of critical systems • Write clean, testable, and resilient code with attention to edge cases and performance • Contribute to technical design documents and participate in design discussions • Participate in code and design reviews and contribute to on-call rotations • Help design and build LLM-powered features and agentic workflows for automated investigation, triage, or remediation assistants • Integrate LLM APIs and agent frameworks into backend services, considering reliability, cost, latency, and evaluation • Contribute to prompt design, tool/function-calling integrations, and guardrails for AI-driven components • Use GenAI coding assistants and agents in the development workflow to accelerate delivery and testing • Collaborate with product managers, designers, and engineers to align on specifications and priorities • Break down well-defined projects into executable steps and drive them to completion • Contribute to roadmap discussions and share ideas for technical improvements • Communicate updates, challenges, and solutions in an async-first environment • Seek feedback and mentorship from senior engineers

🎯 Exigences

• 3–5 years of industry experience as a Software Engineer, with a track record of shipping production backend systems • Solid backend proficiency in Python, with experience building and maintaining production systems • Experience with system design fundamentals and building reliable, scalable applications • Working knowledge of relational databases and modern data storage technologies • Experience with AWS cloud services, including S3 and RDS, and deployment practices • Understanding of service health, monitoring, and incident response practices • Comfortable writing technical documentation and contributing to design discussions • Proactive ownership of assigned work and eagerness to grow into increasingly complex projects • Strong focus on code quality, reliability, monitoring, and performance • Ability to work cross-functionally and in a distributed environment • Genuine interest in LLM-powered features and agentic systems, and willingness to leverage GenAI assistants and coding agents • Exposure to service-to-service communication, such as gRPC and Kafka, and caching with Redis is a plus • Familiarity with containerization and orchestration, such as Docker, Kubernetes, and Helm, is a plus • Hands-on experience integrating LLM APIs, such as OpenAI and Anthropic, into production applications is nice to have • Exposure to agent frameworks or patterns, such as LangChain, LangGraph, tool/function calling, and ReAct-style agents, is nice to have • Familiarity with prompt engineering, evaluation, and observability for AI-driven features is nice to have

🏖️ Avantages

• AI-assisted recruiting tools are used to prepare for candidate interviews, but do not make hiring decisions or screen candidates automatically • Pre-employment checks in line with prevailing legislation and Abnormal AI's security and privacy standards • Equal opportunity employer