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Senior Software Engineer - Canada Only

Technosylva
CAN
Full-time
Senior
Onsite
Discovered 2 weeks ago
awsazuredockergcpjavakubernetes

Full Job Posting

Responsibilities

  • Design, build, and maintain backend services and APIs (REST/gRPC or equivalent).
  • Model, optimize, and maintain relational and non-relational databases — schema design, query tuning, and data integrity.
  • Implement and troubleshoot inter-process communication (IPC, 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

  • Required
  • 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.

Preferred Qualifications

  • 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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