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The DevOps Engineer will design, implement, and manage GCP environments, develop IaC using Terraform, enhance CI/CD pipelines, and ensure cloud security compliance. Responsibilities include migration, optimization, and providing technical guidance to clients.

The Data Engineer will design and develop data solutions for clients, build data pipelines, lakes, DWHs, and implement AI/ML models.

The Backend Engineer will lead AI integration, mentorship, and support in a large R&D environment, focusing on AI tools adoption and SDLC enhancement.

Looking for a C/C++ developer for real-time embedded software, requiring 1-3 years of experience and proficiency in OOP and multithreading.

The Network Expert will design, implement, and maintain network infrastructure, requiring expertise in network security, architecture, and troubleshooting.

Design, build, and maintain scalable microservices and Angular frontends; implement real-time messaging and video streaming features; deploy and operate services on GCP/AWS; optimize APIs and system performance; contribute to architecture, code reviews, and mentor junior engineers.

Lead end-to-end manual QA for data-driven systems and ETL pipelines: web/API testing, complex SQL validation across DWH flows, log analysis, test planning/execution, defect reporting, and using AI tools to generate tests and optimize testing processes.

Own and optimize the core edge software for a hybrid edge-cloud AI video security platform. Implement low-latency video streaming, recording, on-device AI integration, secure edge-cloud communication, and profile and tune performance under resource constraints.

Build and optimize the core edge platform for a hybrid edge-cloud video security system. Develop video streaming, recording, real-time AI processing, low-latency communications, performance profiling, and containerized deployments across resource-constrained devices. Collaborate with AI/ML engineers and perform code reviews, debugging, and performance tuning.

Build and optimize the core edge platform for a hybrid edge-cloud video security system. Develop streaming, recording, and low-latency AI processing, ensure secure edge-cloud communication, profile and optimize CPU/memory under load, and collaborate on deploying on-device models while participating in code reviews and debugging across the stack.