As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.
Requirements:
Your Experience
Backend Engineering: 5+ years of experience building and maintaining production-grade distributed systems.
Languages: Proficiency in Go (Golang) is a strong advantage. We are open to engineers with deep expertise in other backend languages (Java, Python, Rust, C#, or Node.js) who are willing to transition to a Go-primary stack and have a focus on clean, well-tested code.
Fundamentals: Strong grasp of system design, data structures, and algorithms in high-scale cloud environments.
Standards: Experience with CI/CD, comprehensive testing (unit, integration, E2E), and rigorous code reviews.
Cloud: Proficiency in AWS, GCP, or Azure, including cloud-native services.
Reliability: Experience with observability (monitoring, logging, tracing) and system profiling.
Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent technical/military experience.
Advantages
Advanced Go: Deep experience with concurrency and memory management patterns.
Distributed SaaS: Background in managing multi-tenant, cloud-based SaaS at scale.
Cybersecurity: Familiarity with threat detection or cloud security infrastructure.
AI Systems: Interest in agentic workflows or prompt engineering in production.
Your Experience
Backend Engineering: 5+ years of experience building and maintaining production-grade distributed systems.
Languages: Proficiency in Go (Golang) is a strong advantage. We are open to engineers with deep expertise in other backend languages (Java, Python, Rust, C#, or Node.js) who are willing to transition to a Go-primary stack and have a focus on clean, well-tested code.
Fundamentals: Strong grasp of system design, data structures, and algorithms in high-scale cloud environments.
Standards: Experience with CI/CD, comprehensive testing (unit, integration, E2E), and rigorous code reviews.
Cloud: Proficiency in AWS, GCP, or Azure, including cloud-native services.
Reliability: Experience with observability (monitoring, logging, tracing) and system profiling.
Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent technical/military experience.
Advantages
Advanced Go: Deep experience with concurrency and memory management patterns.
Distributed SaaS: Background in managing multi-tenant, cloud-based SaaS at scale.
Cybersecurity: Familiarity with threat detection or cloud security infrastructure.
AI Systems: Interest in agentic workflows or prompt engineering in production.
This position is open to all candidates.
