JumpCloud - Senior Software Engineer, Security Engineering
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Requirements
• SOC / SIEM Empathy: Experience building tools for Security Operations Centers. You understand concepts like "False Positive Fatigue," "Triage," and "Incident Context. • Security & Identity: Exposure to authentication standards (OAuth, OIDC, SAML) or experience building logic for Fraud/Risk engines. • Integrations: Experience integrating with third-party threat feeds (e.g., GeoIP, IP Reputation).
Responsibilities
• Technical Leadership & Architecture: Lead the high-level architecture and low-level design of new Go microservices. You will break down complex requirements, mentor other engineers, and collaborate with senior technical leaders to manage technical debt and feature detailing. • Build the Decision Engine: Architect the services that consume data from our risk engine (Kafka) and determine the appropriate system response in milliseconds. You will build modular components that can be shared internally. • "Think Like a SOC Analyst": You will design API responses and data structures that provide deep context (scores, lineage, threat details) so IT Admins can investigate incidents without guessing. • Prepare the Runway for ML: Utilise Machine learning concepts to harness the inhouse data to build solutions for IT Admins. • Operational Excellence: Own your services in production. You will define SLIs/SLOs, manage database performance (Postgres/Redis), ensure high availability, and perform upgrades to keep up with modern security best practices. • Strategy & Collaboration: Partner with the Platform Engineering team to define data contracts. You will help shape the future of our Identity Management services roadmap by participating in planning conversations with Product Managers. • We’re looking for: • 6-8+ years of backend software development experience. • Expert Proficiency in Go (Golang): You understand concurrency patterns, memory management, and how to build services that scale. • Event-Driven Architecture: Proven experience building systems that consume and produce messages via Kafka, Kinesis, or SQS.Stream Processing: Experience with Apache Flink or Spark Streaming. • Database Fluency: Experience modeling data in both Relational (Postgres) and NoSQL (Redis/DynamoDB) stores. • Cloud Native: Deep experience with AWS services (Lambda, ECS/EKS) and Infrastructure-as-Code (Terraform). • ML Infrastructure Interest: You don't need to be a Data Scientist, but you have a working interest in MLOps or Model Serving. You are excited about building the "pipes" that put ML models into production.
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