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we are looking for a Product Security Engineer.
Responsibilities:
Own, maintain, and continuously improve the Secure Design Review process, ensuring security considerations are integrated early in the development lifecycle.
Develop, implement, and maintain Zenitys Application Security Program, including controls, standards, developer enablement, and automation.
Manage SAST and DAST tooling, including configuration, integrations, alerting, developer workflows, and program-wide reporting.
Monitor and enforce SDLC security controls, ensuring consistent application of secure development practices across all engineering teams.
Develop and maintain Zenitys Cloud Security Program, defining guardrails, policies, and automated controls for secure-by-default cloud deployments.
Manage CSPM tooling, including configuration, findings triage, reporting, and alignment with internal risk and compliance processes.
Partner with DevOps to design, implement, and maintain a fully secured CI/CD pipeline, ensuring that security checks, guardrails, and automated gates are embedded throughout build, test, and deployment stages.
Collaborate closely with engineering teams to deliver actionable guidance, model threats, advise on architecture, and support secure implementations.
Drive automation-first approaches to product and cloud security, reducing friction and enabling fast, safe development.
Define and track KPIs, metrics, and reporting for application and cloud security health.
Identify gaps in product, application, and cloud security posture and drive end-to-end remediation plans.
Promote a culture of security and developer empowerment by delivering clear, pragmatic, and scalable guidance.

We're seeking a Senior Security Researcher & Team Lead to own and drive Zenity's security research domain from the ground up. This is a leadership-first role - you'll build and guide a research team, define a new frontier in AI and agentic security, and shape the methodologies and standards that don't yet exist in the industry. If you thrive in ambiguity, love creating structure where there is none, and want to leave a real mark on an emerging security domain, this role is for you.
You'll investigate emerging attack surfaces, architect and implement detection mechanisms, and validate your findings in production environments protecting Fortune 500 customers. It's a high-ownership position that blends deep technical research with strategic thinking and team leadership - with a real sense of urgency to shape the AI security landscape not just for Zenity, but for the entire security community.
Responsibilities:
Lead and mentor a security research team, driving vulnerability and threat research that generates product value and protects Fortune 500 customers in production environments.
Take end-to-end ownership of detection mechanism design for agentic AI applications - from initial hypothesis through experimentation to production-grade implementation.
Apply expertise across cloud, identity, web, and API security to map and address the evolving AI threat landscape.
Apply LLMs, Agentic AI, and machine learning models to detect security vulnerabilities.
Collaborate closely with engineering and product teams to translate research into actionable, shippable security capabilities.

we are looking for a Senior AI Engineer.
As a Senior AI Engineer on the Guardian Agents team, you will develop both our autonomous "digital employees" that execute security programs and the Control Plane that governs them. You will build a platform that allows customers to calibrate agents through conversation, ensuring human feedback is transformed into persistent organizational knowledge. By engineering these closed-loop systems, you enable agents to learn, evolve, and deliver accurate, goal-driven security outcomes at scale.
Architect Autonomous Agents: Build goal-driven agents for complex security tasks like false-positive reduction and automated triage.
Build the Control Plane: Develop the infrastructure for Human-in-the-Loop (HITL) feedback, natural language calibration, and stateful memory systems.
Engineer for Growth: Implement evaluation frameworks and "organizational memory" to ensure agents stay accurate and follow historical security precedents.
Bridge AI & Engineering: Collaborate in a "Core Pod" with Security Researchers and Data Scientists to turn raw security signals into scalable, productized agent behaviors.
Scale Data Pipelines: Integrate agents with Big Data foundation to ensure real-time context and tenant-safe execution.