Jobs at SAFE Security

Research vulnerabilities and exploits by analyzing intelligence feeds, identifying CVEs with public proofs of concept, building vulnerable labs, testing and porting exploits to Metasploit or Nuclei, and contributing to open-source frameworks. The role also involves tracking emerging attacks, applying LLMs to vulnerability research, and collaborating with threat research and program management teams.

Research newly disclosed and actively exploited vulnerabilities, analyze affected products and trigger conditions, build lab-based proofs of concept and SAFE Query Language detections, coordinate exploit development, identify compensating controls, and monitor emerging threats. The role requires CTF experience, LLM-assisted vulnerability research, security tooling expertise, and contributions to open-source tools, CVE advisories, or published research.

Build production-grade AI agents, automation, and platform capabilities that improve engineering throughput. Identify lifecycle bottlenecks, redesign workflows, integrate AI into development, review, testing, CI, incidents, and operations, and establish security and quality guardrails. Measure improvements in cycle time, deployment frequency, defect rates, and operational toil. The role requires strong software engineering, distributed systems, cloud, CI/CD, LLM, quantitative analysis, communication, cross-team influence, and mentoring skills.

Build and operate Safe’s AI platform, including GPU clusters, Kubernetes infrastructure, inference serving, model lifecycle management, evaluation systems, observability, and secure multi-tenant services. Optimize GPU utilization, latency, throughput, and cost while supporting production LLM workloads. Develop APIs, SDKs, CI/CD workflows, and Terraform-based infrastructure on cloud platforms. Own reliability, security, disaster recovery, incident response, code reviews, mentoring, and end-to-end delivery across platform engineering initiatives.

Lead architecture and hands-on development of secure, scalable, multi-tenant microservices for a cyber risk platform. Mentor engineers, conduct code reviews, solve complex architectural and performance challenges, and build cloud solutions using AWS or comparable platforms. Own technical roadmaps, collaborate cross-functionally with Product, Design, and GTM, drive high-quality delivery, and introduce engineering practices that improve reliability and velocity.

Own post-sale success for enterprise customers using SAFE’s CTEM platform. Serve as a trusted cyber-risk advisor to CISOs, CIOs, risk, compliance, and security operations stakeholders; align success goals, drive value realization and retention metrics, support platform adoption, coordinate deployment issues, document best practices, and communicate customer feedback to Product Management.

Own the global demand generation strategy and pipeline outcomes for an AI-driven cybersecurity platform. Lead ABM, integrated campaigns, paid media, third-party demand, webinars, and virtual programs across enterprise markets. Partner with Sales, RevOps, and Product Marketing on forecasting, account coverage, attribution, and pipeline measurement. Operate and optimize the demand technology stack, manage spend based on ROI, and communicate performance and strategic tradeoffs to executives.

Lead a team of developers to deliver core product features for predicting and preventing cyber breaches, ensuring technical excellence.

As an Engineering Manager, you'll lead a team of engineers, providing technical guidance, strategy, and project management to develop solutions that prevent cyber breaches.

Lead architecture and implementation of enterprise-grade AI systems for cybersecurity: LLM orchestration, RAG pipelines, vector stores, agents, model deployment, evaluation, monitoring, and governance. Partner with platform and data teams, productionize agents, build AI observability and HITL loops, and mentor engineers to deliver explainable, reliable, and secure AI features for enterprise products.

Perform vulnerability research and exploit development: identify CVEs with available exploits/PoCs, build vulnerable labs, port exploits to frameworks (Metasploit, Nuclei), contribute to open-source exploit projects, and collaborate with Threat Research and Program Management while using LLMs for research.

Manage end-to-end People Operations including onboarding/offboarding, HRIS administration (BambooHR), EOR management (Deel), payroll/benefits coordination, performance cycle administration (Leapsome), compliance with U.S. employment laws, reporting/analytics, process improvements, and cross-functional HR program execution to support a global, high-growth SaaS workforce.

Lead and grow an SDET team, define functional testing strategy and infrastructure, champion AI/LLM-driven test generation, maintenance, and analysis, own deployment and CI/CD for production services in containerized AWS environments, perform code reviews, and collaborate with product and engineering to ensure release quality.