Senior Software Engineer

Emploi pas sur LinkedIn

🕒 il y a 1 mois

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Configurer une alerte email pour les nouveaux emplois

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

Horizon3.ai

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2019

🔒 Cybersecurity

🤖 Intelligence artificielle

☁️ SaaS

Cybersecurity • Artificial Intelligence • SaaS

La plateforme NodeZero™ permet à votre organisation de découvrir, corriger et vérifier en continu votre surface d'attaque exploitable. Réduisez votre risque de sécurité en trouvant de manière autonome les faiblesses de votre réseau, en sachant comment les prioriser et les corriger, et en vérifiant immédiatement que vos corrections fonctionnent. NodeZero offre des tests d'intrusion autonomes respectant l'environnement de production et d'autres opérations d'évaluation essentielles qui s'adaptent à vos environnements internes, externes, cloud et cloud hybride les plus vastes. Pas d'agents requis, pas de code à écrire, et pas de consultants à embaucher.

Description

• Build and evolve the agent harness and orchestration that turns an LLM into a reliable autonomous pentester, the loop that reasons over an application, forms attack hypotheses, acts, and verifies results. • Design the tools and tool-shaped feedback the agent uses to probe and exploit, and the structured-output and validation layers that keep it reliable (e.g., hook-enforced mandatory validation, schema-constrained outputs). • Translate the team's offensive expertise into repeatable agent capabilities — partnering directly with our attackers to encode how they think into something the agent can do consistently. • Own and grow our evaluation infrastructure: benchmark suites, a failure-mode taxonomy across the pipeline (discovery → hypothesis → exploitation → verification), and regression detection, so we actually know whether the agent is getting better. • Manage LLM inference in production: model selection, prompt and context engineering, and keeping cost and latency under control (we run on AWS Bedrock with centralized cost tracking). • Hold the line on production-safety and no-false-positives, every finding the agent reports has to be real and reproducible.

🎯 Exigences

• 5+ years building production software, with strong Python. • Hands-on experience building LLM-powered applications or agents, tool use / function calling, structured outputs, multi-step orchestration, and the glue that makes it all hold together. • A track record of making LLMs reliable in production, you've wrestled nondeterminism, designed around model limitations, and shipped something that worked when it mattered. • Real experience with evaluation: you've built or owned the harness that tells you whether a model or agent change is an improvement, not just a vibe. • Strong instincts for prompt and context engineering, and the judgment to keep the model's job small and well-scoped. • Solid software fundamentals — testing, observability, and the discipline to keep a complex agent debuggable. • Ownership mentality, comfortable owning a critical, fast-moving subsystem end to end.

🏖️ Avantages

• Health, vision & dental insurance for you and your family • Flexible vacation policy • Generous parental leave • Growth Opportunities: Be part of a dynamic and growing team with numerous career development opportunities. • Inclusive Team: We value diversity and promote an inclusive culture where everyone can thrive. • Innovative Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking. • Hybrid & Remote Work: We embrace a mix of remote and hybrid work models depending on role and location, including our Chicago office, where some roles require regular in-office presence.