AI Application Engineer
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Minimum qualifications:
- Bachelor’s degree in Computer Science, Data Science, Engineering, a related technical field, or equivalent practical experience.
- 8 years of experience in software development, with a focus on building end-to-end web applications and data pipelines.
Preferred qualifications:
- Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or a related engineering field.
- 2 years of experience in data pipelines and analytics.
- 2 years of experience developing and deploying AI/ML solutions, including AI agents, Large Language Models (LLMs), or advanced statistical models in a production environment.
- Experience in technical leadership, project management, and executive communication.
- Experience setting up manufacturing assembly processes, driving product launches and assembly process optimization within manufacturing operations.
About the job
Build intelligent software solutions that optimize our data center hardware and processes.
In this role, you will go beyond traditional software engineering by building autonomous AI agents and advanced analytics pipelines that turn massive, complex datasets into real-time, actionable business insights. You will serve as a technical lead, collaborating with cross-functional stakeholders to drive automation and innovation.
US: $144000 - $209000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design, develop, and maintain robust, scalable web applications that deliver automated, real-time insights for Google's data center hardware and operational processes.
- Create and deploy intelligent AI agents to automate complex workflows. Lead the foundational development required to power these agents, including data discovery, data quality validation, robust data pipelines, and secure API creation.
- Apply AI/ML techniques and rigorous statistical methods to solve complex operational challenges and predict hardware/process anomalies.
- Partner closely with business leaders and cross-functional teams to deeply understand root needs, translate them into technical roadmaps, and continuously iterate on solutions to maximize business impact.
- Identify inefficiencies and pioneer opportunities to automate manual processes both within the immediate team and across the broader organization.
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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
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