The Role

We are building a real-time threat intelligence platform from the ground up. This is a zero-to-one initiative focused on streaming critical security data to enterprise teams at scale. As an SWE-2 on this team, you won't just be executing on a roadmap, you'll be helping us find the problems that aren't on it yet. We are looking for a backend engineer with a builder mindset who thrives in an environment where they can take ownership and help define the technical path forward.

What You Will Do

• Build & Scale: Develop and maintain high-performance backend services using Python or Golang.
• Stream Real-Time Data: Build and optimize streaming architectures to handle live threat intelligence with low latency.
• Search & Indexing: Implement and tune OpenSearch/Elasticsearch layers to ensure massive datasets are searchable and actionable.
• Define the "How": Take high-level goals and translate them into technical specs and clean, maintainable code.
• Cloud Ownership: Manage your own deployments and infrastructure within AWS/EKS.
• AI-Augmented Development: Use AI tools to speed up development cycles and automate routine backend tasks.
• Collaborative Innovation: Work closely with the team to identify architectural gaps and proactively suggest improvements.

Must Haves

• 3–5+ years of production experience in backend development and systems design.
• Hands-on experience with Kafka, Kinesis, or similar message brokers/streaming platforms.
• Proven experience working with OpenSearch or Elasticsearch at scale.
• Deep familiarity with AWS (highly preferred) and mandatory production experience with EKS (Kubernetes).
• Proficiency in Python or Golang and solid experience with Postgres.
• Builder mindset: comfortable with "zero-to-one" challenges and defining requirements when specs are loose.

Nice to Have

• Frontend Basics: Familiarity with React/TypeScript for building internal tools or data visualizations.
• Security Context: An interest in cybersecurity or experience working with security data.
• Tooling: Experience using modern AI productivity tools to increase engineering velocity.

Education

Bachelor of Science degree in Computer Science, Applied Sciences, Information Systems, or a closely related engineering field.
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