Senior Product Security Engineer

AlphaSense provides an AI-driven market intelligence and search platform that helps sophisticated companies make informed decisions. The Senior Product Security Engineer will lead secure product design and implementation across the company’s AI-native platform, focusing on AI/ML security, secure architecture, threat modeling, security automation, and customer-facing assurance.

Responsibilities:

• Architect and enforce security controls for AI/ML systems — model training, data pipelines, inference environments, and agentic workflows
• Identify and mitigate AI-specific attack vectors: prompt injection, data poisoning, model inversion, model theft
• Implement model provenance, integrity, and auditability controls for responsible, secure AI operations
• Align AI security with governance and compliance teams against frameworks like NIST AI RMF and the EU AI Act
• Embed security throughout the software and AI development lifecycle, partnering with architects, engineering, and product across AlphaSense's application and cloud ecosystems
• Ensure security, privacy, and compliance by design
• Define and maintain secure development standards, guidance, and best practices
• Lead threat modeling, secure design reviews, and risk assessments across the software development lifecycle
• Build and maintain security automation and governance that integrates into development workflows
• Produce customer-facing security assurance — security questionnaire responses, security whitepapers, and trust collateral — that unblocks enterprise deals
• Represent product security in customer, cross-functional, and leadership discussions
• Mentor teams on secure coding, AI risk management, and secure design
• Promote a security-first culture through advocacy, documentation, and training

Requirements:

• 5–7+ years in product, application, or cloud security engineering
• Deep understanding of secure SDLC, threat modeling, and secure architecture design
• Ability to read and review code to inform threat models and design reviews
• Experience securing AI/ML pipelines, data workflows, and model-serving infrastructure, with working knowledge of AI/LLM security (prompt injection, model integrity, provenance)
• Proven expertise with cloud security concepts and best practices across multi-cloud environments
• Familiarity with DevSecOps and CI/CD environments
• Familiarity with encryption fundamentals — symmetric and asymmetric cryptography, TLS/mTLS, key management, and secrets handling
• Understanding of authentication and authorization patterns in modern applications: OAuth 2.0, OIDC, SAML, RBAC, and ABAC
• Demonstrated ability to drive cross-functional security initiatives — partnering with engineering, product, and compliance to embed security into roadmaps, influence architectural decisions, and align stakeholders across boundaries
• Proficiency in Python, Java, and/or JavaScript for security automation and tooling
• Container and orchestration security (Kubernetes runtime protection)
• Software supply chain security and artifact integrity verification
• Experience with bug bounty programs — triaging findings, driving root-cause analysis, and turning results into systemic security improvements
• Familiarity with compliance and governance frameworks (SOC 2, ISO 27001, NIST 800-53, NIST AI RMF)
• Certifications such as CKS, CISSP, CSSLP, or AI/ML security credentials