Optical AI Software Engineer

Join our Network Infrastructure Optical Systems and Networking R&D team as an R&D Software Optical Designer! In this hybrid role, you'll collaborate in our state-of-the-art lab equipped with cutting-edge communications and next-gen R&D tools. Your work will focus on enhancing subsea communications by developing intelligent optical systems that optimize performance during commissioning and predict potential degradation to recommend timely remediation actions. You'll engage with cross-functional teams, including DSP, Systems, and SW engineers, while directly interfacing with customers. Enjoy the benefit of contributing to innovative projects encompassing customer commissioning software, cloud tools, R&D simulations, and design aspects of subsea communication. Be self-motivated and thrive in a highly innovative environment, where your contributions genuinely impact our advancements in the field. Embrace this opportunity to shape the future of communication technology with us at Nokia! Deep knowledge of submarine optical communication systems, including wet plant and dry plant architectures, transmission engineering, system commissioning, capacity upgrades, and lifecycle management of subsea cable networks. Demonstrated ability to use modern AI-assisted development platforms and coding agents to create, test, debug, and maintain software solutions. Experience leveraging generative AI tools to rapidly prototype applications, automate workflows, analyze data, and solve complex engineering problems. Strong understanding of optical power flow analysis and the ability to apply analytical tools and AI-assisted techniques to model and optimize optical networks. Knowledge of Raman and EDFA amplification systems, including their operational characteristics, control strategies, and performance optimization. Familiarity with GN models, optical system simulation, or related analytical frameworks, with the ability to use AI and software tools to develop, interpret, and enhance such models. Proven ability to evaluate AI-generated code and algorithms for correctness, performance, scalability, and maintainability. Strong systems-thinking, troubleshooting, and technical communication skills, with the ability to bridge domain expertise and software-enabled solutions.