[Remote] Senior Product Security Engineer

Note: The job is a remote job and is open to candidates in USA. AlphaSense is hiring a Senior Product Security Engineer to design and implement secure, scalable products across its AI-native platform. The role partners with architecture, engineering, and product teams to embed security throughout the development lifecycle, lead AI security and threat modeling, and support customer-facing security 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

Skills

• 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

Benefits

• Collaborative and security-minded engineering culture
• Career growth opportunities
• You may also be offered a performance-based bonus, equity, and a generous benefits program.

Company Overview

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