Security Engineer - Product Security

Build and improve agentic AI workflows that turn security vulnerability findings into tested, review-ready code changes for engineering teams across Spotify.

Design and implement evaluation frameworks to measure the quality of automated fixes, including correctness, completeness, safety, build and test success, and pull request merge rates.

Develop tools and processes to compare remediation approaches, evaluate AI models, and continuously improve the reliability and effectiveness of generated fixes.

Research and apply emerging practices in AI-assisted vulnerability remediation, including prompt engineering, context engineering, and vulnerability-specific fix guidance.

Identify which vulnerability types are suitable for automated remediation, balancing security impact, technical feasibility, and developer experience.

Collaborate with developers and security stakeholders to collect feedback through code reviews, pull requests, support channels, and interactive sessions, using these insights to improve remediation quality.

Help shape how Spotify approaches security posture management by building scalable solutions that reduce security risks and make it easier for teams to address vulnerabilities.

You have experience in software engineering, particularly within security engineering, developer experience, or internal infrastructure.

You can confidently read, understand, and write code in one or more languages such as Java, Python, Scala, C++, or TypeScript.

You have experience designing and building scalable systems, with an understanding of software architecture and reliable engineering practices.

You have worked with agentic AI systems or AI-assisted development workflows and understand how to apply them to real-world engineering challenges.

You understand common security risks, attack vectors, and vulnerabilities, including those affecting AI and machine learning systems, and approaches to mitigating them.

You have experience integrating security tools or automated workflows into production engineering environments.

You are familiar with agentic AI frameworks and approaches to evaluating the quality, reliability, and safety of AI-generated outputs.

You enjoy collaborating across teams, learning from feedback, and navigating ambiguity. You're comfortable experimenting with new approaches while balancing innovation with thoughtful security decisions.

This role is based in Toronto

We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.