Senior Software Engineer

🔥 2 minutes ago

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 10%

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Logo of Technosylva

Technosylva

51 - 200 employees

Founded 1997

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

<Technosylva> is a provider of AI-driven wildfire and extreme weather risk mitigation software that delivers real-time forecasting, predictive simulations, and incident management tools for electric utilities, fire agencies, and insurers. Their cloud-based products (Wildfire Analyst, Tactical Analyst, fiResponse) offer situational awareness, operational decision support, and risk quantification to help customers plan, operate, and respond to wildfire and severe weather events.

📋 Description

• Design, build, and maintain backend services and APIs (REST/gRPC or equivalent) • Model, optimize, and maintain relational and non-relational databases, including schema design, query tuning, and data integrity • Implement and troubleshoot inter-process communication, messaging, and service-to-service protocols • Develop primary backend systems in C# and Java • Design and implement highly optimized compute models in C++ • Apply synchronization, concurrency, and multi-processing techniques to maximize throughput and correctness • Profile, benchmark, and optimize performance-critical code paths • Translate mathematical and algorithmic requirements into efficient, production-grade code • Participate in architecture decisions, code reviews, and technical mentorship • Write clean, testable, well-documented code and contribute to CI/CD practices

🎯 Requirements

• Strong proficiency in C# and Java for backend development • Strong C++ skills for high-performance compute work • Solid understanding of concurrency, synchronization primitives, threading, and multi-processing • Strong mathematical proficiency — numerical methods, linear algebra, or applied math relevant to compute models • Experience with API design, database design, and IPC mechanisms • Proven ability to profile and optimize compute- and memory-intensive workloads • Experience with parallel and high-performance computing — multithreading at scale, SIMD/vectorization, GPU (CUDA/OpenCL), or distributed compute (MPI) • Background in scientific, geospatial, simulation, or physics-based modeling domains • Familiarity with cloud infrastructure and containerized deployment (AWS/Azure/GCP, Docker, Kubernetes) • Experience building and operating low-latency, high-throughput data or compute pipelines • Working knowledge of observability, testing, and performance-regression practices for production systems

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