Senior Staff Software Engineer, AI Telemetry and Developer Intelligence

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 Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google . Architect canonical, evolution-safe telemetry agreements and schemas building on integration event protos, trajectory schemas, and AI-assisted instrumentation across developer and DevAI surfaces so new agentic tools emit structured, high-signal telemetry by default. Design and build low-latency ingestion, deterministic sampling, Personally Identifiable Information (PII) redaction, and LLM-powered trajectory classification pipelines. Build core attribution engines linking multi-turn agent trajectories, tool calls, skill invocations, token spend, and downstream artifacts including Piper CLs, Critique reviews, Tracker issues, and test runs to power Levels of Autonomy and end-to-end Critical User Journeys. Establish engineering standards across the data and serving stack to eliminate pipeline fragility and enforce data freshness and completeness SLOs. Partner with Engineering Directors, Principal Engineers, Data Scientists, and sibling DevAI/CodeAI platform leads to unblock cross-organization instrumentation bottlenecks, review critical CLs and RFCs, and mentor engineers through example. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 7 years of experience leading technical project strategy, ML design, and end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging). 5 years of experience with design and architecture; and testing/launching software products. 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. Experience designing software architecture for applications, including AI/ML systems. Preferred qualifications: Experience designing and building distributed systems. Experience programming in C++, Java, Protocol Buffers, and SQL data pipelines. Experience designing and operating distributed data telemetry systems, streaming or batch ingestion pipelines, or observability infrastructure. Experience translating difficult technical challenges into production architectures with measurable reliability and adoption. Experience with AI or Large Language Model agent architectures, agent trajectory logging, and evaluation pipelines. Experience designing privacy-preserving analytics systems and high-performance analytical serving layers.