Staff Software Developer, Generative AI, Applied AI
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development with C++.
- 7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with design, architecture and testing/launching software products.
- 2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal) or with GenAI-related concepts (e.g., language modeling, computer vision).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex organization involving cross-functional, or cross-business projects.
About the job
Google Cloud's software developers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for software developers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software developer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our software developers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Our agile Artificial Intelligence (AI) team seeks a highly motivated AI Research Developer passionate about managing issues and delivering innovative solutions at breakneck speed. We develop agentic AI solutions for impactful enterprise use cases. In this role, you will be inventing, designing, and deploying systems, focusing on algorithmic innovations for sophisticated agentic AI. This includes improving performance on high-priority directions like multi-agent systems, reinforcement learning, multimodal reasoning, data-centric approaches, evaluation innovations, and enhancing Large Language Model reliability and tool use for enterprises. Your work will directly influence the next wave of AI innovation, turning research into practical, high-impact solutions that solve critical real-world issues.
Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.Responsibilities
- Drive the technical strategy, architecture, and execution for ambiguous projects on our conversational Artificial Intelligence platform. Define the technical roadmap for scalable, long-term solutions.
- Act as the lead developing partner for product management and User Experience. Define product strategy, refine ambiguous customer needs into concrete technical designs, and drive consensus across teams.
- Manage and iterate on new platform capabilities to meet immediate customer needs.
- Balance this speed with long-term technical health, advocating best practices to ensure solutions are clean, maintainable, scalable, testable, and easy to refactor.
- Leverage user empathy to guide product direction, respond thoughtfully to customer feedback, and build intuitive, powerful, and seamless experiences for the developers who rely on our platform.
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