Senior Staff Software Engineer, AI Telemetry and Developer Intelligence

Google•San Jose, CA

3d•$262,000 - $364,000

About The Position

Google is seeking a senior staff software engineer for AI telemetry and developer intelligence. The role focuses on building the technical foundations that make agentic tools across developer and DevAI surfaces emit useful, structured telemetry by default. It includes designing canonical telemetry agreements and schemas; developing ingestion, sampling, privacy redaction, and trajectory-classification pipelines; and building attribution systems that connect agent activity with downstream engineering artifacts. The engineer will establish standards for data and serving systems and work across organizations to resolve instrumentation challenges, review technical proposals and changes, and mentor engineers. The position is part of Google’s Core team, which builds and maintains shared technical foundations, developer platforms, product components, and infrastructure used across Google products. The role requires leadership in software development, machine learning strategy and systems, architecture, and product testing and launch.

Requirements

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, including model deployment, model evaluation, data processing, and debugging.
5 years of experience with design and architecture, and testing and launching software products.
5 years of experience in one or more of speech/audio, reinforcement learning, ML infrastructure, or another ML specialization.
Experience designing software architecture for applications, including AI/ML systems.

Nice To Haves

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.

Responsibilities

Architect canonical, evolution-safe telemetry agreements and schemas based 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 support Levels of Autonomy and end-to-end Critical User Journeys.
Establish engineering standards across the data and serving stack to reduce pipeline fragility and enforce data freshness and completeness SLOs.
Partner with Engineering Directors, Principal Engineers, Data Scientists, and DevAI/CodeAI platform leads to resolve cross-organization instrumentation bottlenecks, review critical CLs and RFCs, and mentor engineers by example.