Application Security Engineer
Cerebras Systems2 months ago
Responsibilities
- Own and continuously improve vulnerability management across applications, dependencies, containers, operating systems, cloud infrastructure, and externally exposed services.
- Use AI agents and advanced security models to support vulnerability discovery, code analysis, adversarial testing, prioritization, and remediation.
- Analyze vulnerabilities using exploitability, exposure, affected assets, mitigations, business impact, and threat intelligence rather than scanner severity alone.
- Partner with engineering teams to triage findings, determine remediation, and drive closure within risk-based SLAs.
- Build automation for vulnerability ingestion, deduplication, enrichment, prioritization, assignment, remediation tracking, and reporting.
- Identify systemic vulnerability patterns and address root causes with engineering teams.
- Operate and improve SAST, SCA, secrets detection, container scanning, infrastructure scanning, and external attack-surface monitoring capabilities.
- Validate findings through technical investigation and hands-on testing, including distinguishing exploitable vulnerabilities from false positives and low-risk findings.
- Perform targeted application security reviews and testing for high-risk services and features.
- Integrate security controls into CI/CD and developer workflows while minimizing unnecessary friction.
- Develop metrics and reporting for vulnerability exposure, remediation performance, recurring vulnerability classes, and security risk.
- Evaluate and integrate new security technologies as the software and infrastructure environments evolve.
- Partner with security and engineering teams on incident response involving actively exploited vulnerabilities or urgent remediation.
Requirements
- Strong application security or product security fundamentals with hands-on vulnerability management experience.
- Understanding of vulnerability classes and exploitation techniques across web applications, APIs, authentication systems, cloud services, containers, and software supply chains.
- Ability to read and reason about code and work effectively with software engineers on remediation.
- Experience with vulnerability scanning and application security technologies such as SAST, SCA, DAST, secrets scanning, container scanning, or CSPM.
- Understanding of CVSS, exploitability, asset criticality, internet exposure, compensating controls, and threat intelligence.
- Ability to manually investigate security findings rather than relying exclusively on scanner output.
- Ability to automate security workflows using Python, Go, or similar programming languages.
- Experience integrating security tooling into CI/CD and modern software development workflows.
- Comfort working with Linux, Git, containers, and cloud environments.
- Ability to communicate security risk clearly to security specialists and engineering teams.
- Automation-first mindset focused on scalable solutions.
- Preferred experience securing AI/ML platforms, inference services, or large-scale compute infrastructure.
- Preferred experience building or operating vulnerability management programs at scale.
- Preferred experience with AWS, Kubernetes, Docker, and cloud-native environments.
- Preferred experience with software supply-chain security, dependency management, GitHub, CI/CD security, threat modeling, secure design reviews, penetration testing, offensive security, external attack-surface management, vulnerability research, exploit validation, security data pipelines, APIs, workflow automation, LLMs, AI agents, or AI-assisted security tooling.
Benefits
- Opportunity to build security for a breakthrough AI platform and one of the world's fastest AI supercomputers.
- Opportunities to publish and open source cutting-edge AI research.
- Job stability with startup vitality and a simple, non-corporate work culture.
- Inclusive environment with continuous learning, growth, and support.
About Cerebras Systems
Cerebras Systems designs and sells AI compute systems built around its wafer-scale WSE-3 processor, delivered as the CS-3 appliance and via the Cerebras Cloud. It targets enterprises, model labs, and government users needing fast training and inference, and offers on‑prem and cloud deployments. Privately held and headquartered in Sunnyvale, California, the company announced a multi-year partnership with OpenAI to deploy large-scale inference capacity.