Product Operations Specialist, Systems and Data

Intrinsic•Mountain View, CA

5d•Remote

About The Position

Intrinsic is an AI robotics group at Google aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core. Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics. Role As a Product Operations Specialist focusing on Systems and Data, you will optimize Intrinsic’s execution health by building, maintaining, and scaling the tools and automated workflows that power our product development lifecycle. You will have the opportunity to collaborate closely with talented people across Intrinsic’s Product and Engineering functions. You will play a key role in designing and implementing systems that eliminate manual data entry, streamline day-to-day processes, and provide reliable metrics on execution health. To achieve that, you will work closely with Product Managers and Engineering Team Leads to understand their operational bottlenecks and build targeted solutions (e.g., dashboards, scripts, AI workflows). You will hold the tension between giving teams the flexible tooling they need to maintain autonomy while ensuring our systems enforce a standardized, predictable flow of data for Intrinsic overall. Within Product and Engineering operations, you will continuously evolve our internal systems—from scoping and designing updated data structures and workflows, to rewriting legacy scripts and implementing agentic automations.

Requirements

Experience managing systems, automations, and data for product, engineering and/or business operations, including creating automated workflows (Python, AppScript, AI tools, etc) and data analysis dashboards and reports (SQL, BigQuery, Tableau, etc).
Familiarity with the software product development life-cycle and workflows: collecting and writing product requirements, feature planning breakdown, Github collaboration flows, CI/CD workflows, testing, QA, and release processes.
Experience working with agile product and engineering development and management methodology (Scrum, Kanban, etc.) and comfortable with the systems/tools used to manage them (e.g., JIRA, Confluence, etc).
Excellent organization, time management, and analytical problem-solving skills, with adaptability in the face of unknowns and new information.
Clear communication skills with the ability to articulate complex systems and interpret data for both technical and non-technical audiences.
Bachelor's degree in a technical field or equivalent industry experience.

Nice To Haves

Experience leveraging LLMs and AI tools (e.g., Gemini, Claude) to build agentic workflows and automate manual operational tasks.
Experience working at the intersection of Commercial/Business Operations and Product/Engineering Operations.
Experience working with or establishing agile processes in relation to both hardware and software products (e.g., robotics, automation).
Strength in facilitating alignment of competing needs, stakeholders, and constraints by leveraging critical thinking and engaging confidently in trade-off discussions.
Exceptionally organized and self-driven, with a strong sense of ownership and adaptability.

Responsibilities

Design, build, and maintain automated data dashboards and reports to provide reliable insights on execution health and resource allocation.
Develop and manage scalable systems and automations that support agile product development workflows, ensuring seamless tracking from roadmap to development to QA and release.
Experiment with and implement AI tools (e.g., Gemini) to build agentic workflows that automate operational burdens, improve operational excellence and surface new business and product insights.
Collaborate with cross-functional stakeholders to articulate systems and processes, interpret data for different audiences, and translate operational needs into technical tooling requirements.
Guide teams on system best practices and collect feedback to continuously iterate on and improve Intrinsic’s internal tools.
Facilitate alignment across teams to ensure that our systems effectively capture cross-team dependencies and mitigate execution risks.