Backend-focused Senior Software Engineer building C#, Java, and C++ services for Technosylva’s wildfire and extreme weather risk mitigation platform. Optimizing concurrent compute models, APIs, databases, and simulation workloads.
Responsibilities
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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