Note: The job is a remote job and is open to candidates in USA. Stellar Cyber is a fast-growing global cybersecurity company providing an AI- and automation-powered SecOps platform trusted by enterprises, government agencies, and MSSPs. The Senior Software Engineer will own integration domains end-to-end and build production-grade, microservice-based integrations using APIs, streaming technologies, and AI-native patterns. The role also involves leveraging AI tools to accelerate development, automate engineering tasks, and promote AI adoption across the team.
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
- 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
Skills
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 3+ years of backend software development experience
- 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
Benefits
- Ample career growth opportunities
Company Overview
Company H1B Sponsorship