Senior Staff Software Engineer, AI Telemetry and Developer Intelligence

About the role

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.

ABOUT THE JOB:

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

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• 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.