Bachelor's degree or equivalent practical experience.
8 years of software development experience.
7 years leading technical project strategy and end-to-end Machine Learning processes.
5 years in software design, architecture, and product testing/launching.
5 years with Speech/audio technology, reinforcement learning, or ML infrastructure expertise.
Experience in designing software architecture for AI/ML applications.
Responsibilities
Architect telemetry agreements and schemas for AI-assisted instrumentation.
Design low-latency ingestion and PII redaction pipelines.
Build attribution engines linking multi-turn agent trajectories and tool calls.
Establish engineering standards to enhance data pipeline reliability.
Collaborate with cross-functional teams to resolve instrumentation bottlenecks.
Benefits
Comprehensive health and wellness programs.
Generous paid time off and parental leave.
Retirement savings plans with company matching.
Professional development opportunities and training.
Access to cutting-edge technology and resources.
Full Job Description
info_outline X In most instances, this position requires in-person interviews as part of the hiring process
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.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
