Note: The job is a remote job and is open to candidates in USA. AlphaSense delivers AI-driven market intelligence and search to help sophisticated companies make informed decisions. The Senior Product Security Engineer will lead secure, scalable product design across the company’s AI-native platform, embedding security throughout the software development lifecycle. The role focuses on AI/ML security, secure architecture, threat modeling, automation, customer-facing security assurance, and security leadership.
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
- Opportunity to shape and drive product security strategy.
- Collaborative and security-minded engineering culture.
- Career growth opportunities.
- Performance-based bonus.
- Equity.
- A generous benefits program.
Company Overview
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