Senior AI Security Engineer

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dataSpring Inc.

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2009

🤝 B2B

📣 Marketing

☁️ SaaS

B2B • Marketing • SaaS

dataSpring est un fournisseur de services de recherche de marché et de panels en ligne, centré sur l'Asie. Il offre une couverture étendue dans 12 pays avec plus de 2 millions de panélistes actifs, fournissant aux chercheurs des panels propriétaires, des partenaires tiers, et une intégration API. dataSpring propose une plateforme de recherche mobile, un soutien opérationnel régional 24h/24 et 7j/7 dans les langues locales, un système de vérification de la qualité pour la validité des données, des livres de panels téléchargeables, et du contenu d'analyse (blogs et podcasts) ciblé sur les entreprises menant des enquêtes et des recherches de marché en Asie.

Description

• Lead threat modeling for AI capabilities, agentic features, and integrations. • Maintain a living threat model aligned to OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF, and translate findings into prioritized, actionable controls. • Own and maintain the AI security reference architecture covering model hosting, orchestration, tool use, MCP server deployments, and observability. • Establish security patterns for new capabilities before they reach production. • Evaluate foundation models for data-leakage risk and supply-chain provenance. • Harden prompt pipelines against injection, jailbreaking, and context poisoning. • Define trust boundaries, tool call authorization, privilege scoping, and human-in-the-loop escalation policies for multi-agent systems. • Apply zero-trust principles to all model API calls, vector store queries, and external tool invocations. • Classify and control data flowing into LLM context windows, vector databases, and training pipelines. • Instrument AI infrastructure with behavioral telemetry. • Support SOC 2, HIPAA, ISO 27001, and NIST AI RMF compliance as applied to AI systems.

🎯 Exigences

• 8+ years of progressive information security experience across architecture, application security, identity, and data domains. • Hands-on use of Claude for application development, including system prompt design, tool-use configuration, and multi-agent orchestration. • Experience with the Model Context Protocol (MCP) ecosystem and securing MCP server deployments. • Red team or adversarial AI testing experience: model evasion, adversarial examples, jailbreak research. • Background in a regulated industry with data sensitivity requirements, healthcare a plus. • Contributions to AI security open-source projects, published research, or conference presentations (DEF CON AI Village, Black Hat, NeurIPS). • Demonstrated success securing AI/ML systems, LLM applications, or agentic AI platforms in a production environment. • Demonstrated experience building or securing applications developed substantially through LLM-assisted code generation (Claude, Copilot, Cursor, or equivalent). • Cloud-native security experience on at least one major provider (AWS, Azure, GCP), including IAM policy design, network segmentation, and secrets management. • Demonstrated success automating adversarial testing infrastructure include jailbreak suites, prompt injection harnesses, and regression pipelines tied to model and prompt changes. • Relevant certifications: CISSP, CCSP, OSCP, AWS/Azure Security Specialty, or emerging AI security credentials.

🏖️ Avantages

• medical, dental, and vision coverage • a 401(k) with company contributions and matching • paid parental leave • tuition assistance • generous paid time off