AI Application Engineer

Google Google · Big Tech · Austin, TX +1

This role focuses on building AI agents and advanced analytics pipelines to optimize data center hardware and processes, turning complex datasets into actionable insights. The engineer will lead foundational development for these agents, including data pipelines and API creation, and apply AI/ML techniques to solve operational challenges and predict anomalies. The role also involves partnering with stakeholders to drive automation and innovation.

What you'd actually do

  1. Design, develop, and maintain robust, scalable web applications that deliver automated, real-time insights for Google's data center hardware and operational processes.
  2. 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.
  3. Apply AI/ML techniques and rigorous statistical methods to solve complex operational challenges and predict hardware/process anomalies.
  4. 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.
  5. Identify inefficiencies and pioneer opportunities to automate manual processes both within the immediate team and across the broader organization.

Skills

Required

  • software development
  • building end-to-end web applications
  • data pipelines

Nice to have

  • data pipelines
  • analytics
  • developing and deploying AI/ML solutions
  • AI agents
  • Large Language Models (LLMs)
  • advanced statistical models
  • production environment
  • technical leadership
  • project management
  • executive communication
  • setting up manufacturing assembly processes
  • driving product launches
  • assembly process optimization
  • manufacturing operations

What the JD emphasized

  • building autonomous AI agents
  • advanced analytics pipelines
  • real-time, actionable business insights
  • automate complex workflows
  • data discovery
  • data quality validation
  • robust data pipelines
  • secure API creation
  • AI/ML techniques
  • rigorous statistical methods
  • predict hardware/process anomalies
  • automate manual processes

Other signals

  • AI agents
  • autonomous agents
  • advanced analytics pipelines
  • real-time actionable business insights
  • automate complex workflows
  • data discovery
  • data quality validation
  • robust data pipelines
  • secure API creation
  • AI/ML techniques
  • rigorous statistical methods
  • predict hardware/process anomalies
  • automate manual processes