Sr Staff Platform Engineer

Job Overview:

As a Senior Engineer, you will be responsible for maintaining and evolving the core Edge Platform that supports real-time data processing and integration with cloud-based services. You’ll work on optimizing platform performance, solving complex engineering challenges, and ensuring the platform can scale to meet the growing demands of building management systems. Your role will also involve collaborating with cross-functional teams to ensure the platform’s continued success.

Key Responsibilities:

• Platform Maintenance & Optimization: Maintain and optimize the Edge Platform to ensure high reliability, low latency, and performance at scale.
• System-Level Development: Write high-performance, scalable code in Rust, Python, C++  (Optional), and Java (Optional), to enhance platform capabilities.
• Edge Computing Expertise: Work on optimizing the platform for real-time data processing from various building systems with a focus on low-latency, high-throughput solutions.
• Scalability & Performance: Drive system optimization efforts to scale the platform efficiently and ensure robust performance under high data loads.
• Cross-Team Collaboration: Partner with DevOps, backend, and cloud engineering teams to ensure seamless integration and deployment of edge services.
• Security & Stability: Ensure the platform remains secure, stable, and up-to-date, implementing necessary patches and enhancements.
• Mentorship & Leadership: Provide technical mentorship to junior engineers and guide architectural decisions for complex systems.
• Troubleshooting & Debugging: Take ownership of resolving performance bottlenecks, platform issues, and complex bugs across the system.

Required Skills and Experience:

• 6+ Years of Experience in platform engineering or systems development, with a strong background in maintaining high-performance, scalable platforms.
• Proficiency in Multiple Languages: Deep expertise in Rust, C++ (Optional), and Java (Optional), with the ability to write optimized, low-latency code.
• Edge Computing: Strong understanding of edge computing principles, including real-time data processing, distributed systems, and system performance optimization.
• Scalability & Distributed Systems: Experience designing and maintaining distributed systems that can scale to handle large volumes of data with minimal latency.
• Cloud & Containerization: Familiarity with Docker, Kubernetes, and cloud-based environments (AWS, Azure, Google Cloud) to deploy and manage platform services.
• Debugging & Profiling: Expertise in system-level debugging, profiling, and performance tuning for high-throughput, low-latency applications.
• Security: Experience in implementing security measures and best practices for platform stability and data integrity.
• Version Control: Proficient in Git and familiar with modern development workflows.

Nice to Have:

• Real-Time Data Processing: Experience with frameworks or platforms like Apache Kafka, Apache Flink, or Google Dataflow for real-time stream processing.
• Machine Learning: Familiarity with integrating machine learning models into edge computing environments.
• CI/CD Pipelines: Experience with CI/CD practices and tools (Jenkins, GitLab CI, etc.) for continuous integration and deployment.
• Monitoring & Logging: Knowledge of monitoring systems (e.g., Prometheus, Grafana) to ensure platform health and performance.