Senior/ Staff Integration Software Engineer

Stellar Cyber is seeking a Senior/Staff Software Engineer to own integration domains on its AI-driven SecOps platform. The role focuses on delivering production-grade microservice integrations with cybersecurity tools and third-party services, while using AI to accelerate engineering workflows and support platform scalability.

Responsibilities:

• We are looking for a Senior/ Staff Software Engineer to take ownership of one or more integration domains on our Automation-Driven Open & Unified SecOps Platform (powering our AI-driven SIEM, NDR, Open XDR, and Multi-Layer AI)
• This role requires delivering robust, production-grade integrations that support our growing customer base, while driving forward so the platform can scale to the next level
• You will deliver microservice-based solutions spanning both traditional and AI-native integration patterns—REST, GraphQL, streaming APIs, MCP, and LLM-powered automation—connecting our platform with a wide range of cybersecurity tools and third-party services
• Own one or more integration domains end-to-end: roadmap, architecture decisions, trade-offs, and delivery. You identify what needs solving, scope it, and drive it to completion
• Accelerate your own design and development workflow using LLM-based coding assistants, AI-driven testing, and automated code review
• Automate repetitive engineering tasks—builds, deployments, monitoring, incident triage—using AI and scripting, so the team spends more time on high-value work
• Champion AI adoption across the team: help colleagues integrate AI tools into their daily work, build internal tooling where it adds leverage, and measure the efficiency gains

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 5+ years of backend software development experience, with 1+ years as a technical lead or proven experience in taking full ownership of a project
• Proficiency in Python, Go, or Java with a strong foundation in building and operating microservices in production
• Deep experience with API design and integration—both traditional (REST, GraphQL, streaming) and AI service integration (LLM APIs, embedding services)—including secure API patterns (OAuth, API keys, rate limiting)
• Strong background in distributed systems, message queues (Kafka, RabbitMQ), or orchestration frameworks (Celery, Airflow, or similar)
• Demonstrated ability to use AI tools (e.g., Copilot, Cursor, Claude, ChatGPT) to meaningfully accelerate engineering workflows—not just experimentation, but regular use in production work. You have the judgment to know when AI output is trustworthy and when it needs human expertise
• Experience in cybersecurity domains: SOAR, EDR, SIEM, XDR, or similar
• Hands-on experience with large-scale data processing, real-time pipelines, or event-driven architectures
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerized deployments (Kubernetes, Helm)
• Experience with AI-native integration patterns—such as MCP (Model Context Protocol), function calling, or agent orchestration frameworks—or hands-on experience building systems that incorporate LLMs or AI services into workflows or product features