Job Description:
At Motorola Solutions, we believe that everything starts with our people. We're a global close-knit community, united by the relentless pursuit to help keep people safer everywhere.
We're looking for a skilled Senior Full Stack Engineer to build and enhance the core applications that power our AI-driven solutions.
• Develop and enhance React frontends and Node.js backends that serve as the foundation for, and increasingly integrate, advanced language model capabilities and Generative AI services.
• Engineer and maintain critical, well-tested APIs for core platform functionalities, data exchange, and LLM inference, supporting integration with internal ML teams and partners.
• Create internal dashboards and tools that support core development and streamline our research-to-production pipeline for AI models, including tools for prompt engineering and testing.
• Architect backend systems for managing core application data, user interactions, and preparing for the integration of model outputs and vector databases for Retrieval Augmented Generation (RAG), with a strong focus on data privacy and responsible AI.
Your Responsibilities:
Lead the development of intuitive and performant React frontends and Node.js backends for our platform, incorporating LLM-powered applications and Generative AI features.
Architect, build, and maintain robust and scalable web APIs using Node.js (Hapi.js) for core services and AI service delivery.
Design relational database schemas and implement efficient queries supporting evolving ML workflows.
Integrate applications with various internal services, third-party APIs, and data sources, with an increasing focus on language model services.
Develop internal tools that improve development velocity for the core platform and facilitate the efficient transition from AI experimentation to deployment.
Champion software quality through comprehensive testing and contribute to CI/CD processes for both core platform and AI-driven systems.
Collaborate with product managers on core platform features and with ML developers and AI researchers to define requirements for integrating AI capabilities.
Take ownership of full-stack features from conception to deployment, monitoring, and iteration, including projects with a significant AI component.
Contribute to technical architecture decisions for the platform, ensuring its capability to support current and future AI applications.
