Principal Software Engineer - Integration

Stellar Cyber is a global cybersecurity company providing an AI- and automation-driven SecOps platform. The Principal Software Engineer will own integration domains end to end, make architectural decisions, mentor engineers, and deliver scalable microservice-based integrations across traditional and AI-native APIs and third-party cybersecurity services.

Responsibilities:

• 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
• Make the architectural calls—system boundaries, API contracts, reliability targets, build-vs-buy trade-offs—that require deep judgment and context no AI can replace
• Serve as a technical mentor to the engineering team—through design reviews, pairing sessions, and code reviews—with a focus on growing engineers' ability to independently own projects and make sound design decisions
• Set technical direction and champion engineering rigor across the team: quality, documentation, and best practices in secure coding and distributed systems
• 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
• 8+ years of backend software development experience, with 3+ years in a Staff-level or tech lead role where you owned a domain or led a team
• 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
• Track record of mentoring engineers and raising the technical capabilities of a team
• Excellent system design, debugging, and communication skills. You can explain complex trade-offs clearly to both engineers and product stakeholders
• 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