Software is being rewritten in real time. AI agents are starting to write more code than humans do, at a speed no security team has ever had to match, and that single shift is opening up the biggest opportunity our industry has seen in a decade. We're not bracing for it, we're building the company that owns it.
Snyk is building the next generation security platform where security isn't a set of tools people operate. It's a team of security agents working alongside your engineers, finding, fixing, and governing risk at the speed software is now built. These agents work alongside both the company build and the agents they adopt. Security stops being a queue of work waiting for people, and becomes a coordinated workforce companies direct and trust.
Research and exploit weaknesses in LLM applications and autonomous agents. Build attack tooling, agent harnesses, and reproducible evaluations that turn offensive research into measurable improvements in AI security and improve on Snyk’s offensive security product offering.
Looking for candidates with experience in the following areas:
AI red teaming: Prompt injection, jailbreaks, data leakage, tool abuse, and multi-step adversarial attacks.
Offensive security: Web/API penetration testing, authentication and authorization flaws, business logic attacks, and exploit chaining.
LLM fundamentals: Model behavior and limitations, inference, context management, retrieval, and tool calling.
Harness engineering: Agent orchestration, tool integrations, state management, sandboxed execution, and reproducible runs.
Agent security: Trust boundaries, permissions, memory poisoning, scope enforcement, and guardrail bypass testing.
Evals and benchmarks: Realistic attack scenarios, ground truth, reliable graders, dataset quality, and regression suites.
Experimental design: Controlled comparisons, repeated trials, attack success rates, precision/recall, and cost/performance measurement.
Research engineering: Strong Python, APIs, containers, browser automation, and building maintainable research tools.
Failure analysis: Inspecting prompts, traces, and tool outputs to distinguish model, harness, and environment failures.
Exploit validation and reporting: Reproducible proofs of concept, demonstrated impact, false-positive analysis, and actionable remediation.
Collaboration and communication:
Collaborative research: Experience delivering research in a team and translating findings into actionable recommendations that shape priorities and strategy.
Written and verbal communication: Clearly communicate complex research findings, risks, and tradeoffs to technical and non-technical stakeholders.
Snyk is committed to creating an inclusive and engaging environment where our employees can thrive as we rally behind our common mission to make the digital world a safer place. From Snyk employee resource groups, to global benefits that help our employees prioritize their health, wellness, financial security, and a work/life blend, we aim to support our employees along their entire journeys here at Snyk.
Snyk is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Own post-training research for legal AI models, developing SFT and reinforcement learning methods, reward systems, and evaluations to improve long-horizon reasoning and agentic workflows.
Design and deliver production-grade optimization models and solver services for enterprise contact center workforce planning, scheduling, staffing, coverage, and resource allocation.
Design and deliver production-grade optimization models and solver services for workforce planning, scheduling, staffing, and resource allocation in a large-scale contact center environment.
Design and deliver production-grade optimization models and solver services for workforce planning, scheduling, staffing, and resource allocation in a large-scale contact center environment.
Design and deliver production-grade optimization models and solver services for workforce planning, scheduling, staffing, and resource allocation in a large-scale contact center environment.
