Senior Software Engineer, Agentic Planning and Memory

GoogleMountain View, CA
2d$174,000 - $252,000

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers 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 engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers 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. The Agentic Planning and Memory team is transforming Google Workspace into a proactive digital partner. Our mission is to build next-generation agentic capabilities focused on two core pillars: first, developing advanced, general function-calling approaches that allow agents to autonomously execute workflows to process and understand Workspace context; and second, building an agentic memory layer that enables agents to retain and utilize context more efficiently to improve accuracy, personalization, and latency. AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world. The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google [https://careers.google.com/benefits/].

Requirements

  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience programming in Python or C++.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  • 1 year of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision) and with agentic architectures.

Nice To Haves

  • Master's degree or PhD in Computer Science or related technical field.
  • 5 years of experience with data structures and algorithms.
  • 1 year of experience in a technical leadership role.
  • Experience developing accessible technologies.

Responsibilities

  • Design and architect highly available systems for agentic planning and memory management.
  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Set the technical direction for specific workstreams focused on agentic intelligence.
  • Ensure the reliability and performance of agentic workflows and memory retrieval systems.
  • Implement production-level code for advanced function-calling and memory architectures.
  • Identify and resolve technical debt within the planning and memory subsystems.
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