Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market. Position Overview We are looking for a highly skilled Staff Machine Learning Software Engineer with a passion for building robust and scalable systems to power Stellar Cyber’s Open XDR platform. In this role, you will be at the forefront of data-intensive cybersecurity and machine learning software architecture innovation, responsible for developing the foundational components that enable effective and efficient cybersecurity operations for our customers. Key Responsibilities - Design and implement scalable data processing components and supporting features for Stellar Cyber’s cybersecurity applications, including but not limited to, threat detections, incident correlation, threat intelligence, and asset management. - Candidates who successfully pass all the interviews will be assigned to a project area in need. - Monitor and resolve production stability issues related to the aforementioned components and features. - Collaborate closely with machine learning / security researchers, UI / UX, and product management to ensure the design and implementation to align with evolving product needs and business goals.

Location: San Francisco or worldwide On-site/Remote | Full-time Compensation - Full Stack Engineer (remote Worldwide) -$100K – $180K • 0.05% – 0.25% - Full Stack Engineer (Onsite in San Francisco) - $140K – $200K • 0.05% – 0.25% - Senior Full Stack (Remote in the US) - $180K – $250K • 0.05% – 0.25% Our client is a high-growth security startup building the open-source infrastructure used by developers worldwide to manage sensitive configurations and credentials. Backed by premier Silicon Valley investors, the company is on a mission to simplify security for the AI era, currently supporting billions of secure transactions every month. The team are seeking an exceptional Full Stack Engineers and Senior Full Stack Engineers to join the team. In this role, you will work closely with the CTO to build, optimize, and expand the foundation of a global security platform. This position is ideal for an engineer who wants to be a defining piece of a team scaling toward massive market adoption over the next 18 months. Key Responsibilities - Full Stack Engineering: Build and optimize core platform features using modern web technologies. - New Product Development: Help expand specialized security offerings, including Public Key Infrastructure (PKI) and secure SSH access tools. - Security Innovation: Develop strategies for dynamic secret rotation and secure gateways to private resources. - Collaborative Design: Work directly with the CTO to make key technical decisions and establish the company's long-term technical roadmap. - Customer Engagement: Communicate directly with enterprise users to translate high-level security needs into production-ready features.

• design and implement platform solutions in the Innovation Lab • collaborate with cross-functional teams • develop cutting-edge technologies and frameworks • ensure seamless integration of diverse systems • proactively identify bottlenecks and performance issues • contribute to development processes and tools • streamline deployment pipelines • stay current with industry trends • mentor collaborative team members • create clear technical documentation

• Design, develop, and maintain scalable backend services using Python • Build and optimize reliable data pipelines for ingestion, transformation, and analytics • Develop and maintain RESTful APIs using FastAPI • Work extensively with Snowflake and Databricks for data storage, querying, and optimization • Collaborate with product and engineering teams to design data models, APIs, and system integrations • Ensure performance, scalability, reliability, and observability of data services • Implement best practices for code quality, testing, monitoring, and documentation • Participate in code reviews, architectural discussions, and technical decision-making • Troubleshoot and resolve production issues related to data workflows and backend services