Software Engineer, AI Application and Agentic Development

Google Google · Big Tech · New Taipei, Banqiao District, New Taipei City, Taiwan

Software Engineer role focused on building AI-driven tools and infrastructure for testing Pixel devices. The role involves creating autonomous agents, developing scalable AI-native infrastructure, and integrating AI into CI/CD pipelines and HIL systems. Emphasis on agentic development, LLMs, and internal productivity tools.

What you'd actually do

  1. Build autonomous and semi-autonomous agents to handle complex software development and testing tasks, such as black/white box test generation, bug triaging, root-causing, and quality trend/risk analysis, etc.
  2. Develop scalable AI-native infrastructure to elevate testing accuracy and efficiency using LLMs and AI models, ensuring low latency and high reliability for global testing teams.
  3. Create intuitive internal tools, agentic skills, and APIs that allow non-AI experts to leverage machine learning for their work.
  4. Collaborate with Pixel software and hardware teams to integrate AI-driven testing into the existing CI/CD pipelines and hardware-in-the-loop (HIL) systems.

Skills

Required

  • software development
  • programming languages
  • AI-driven tools
  • LLMs
  • AI models
  • CI/CD pipelines
  • hardware-in-the-loop (HIL) systems

Nice to have

  • multi-agent systems
  • complex tool-use
  • function calling
  • model quantization
  • context engineering optimization
  • grounding
  • efficient information retrieval
  • SQL
  • NoSQL
  • vector databases
  • Pinecone
  • Weaviate
  • Vertex AI Vector Search
  • Android internal architectures
  • mobile device testing
  • hardware-software integration
  • product development lifecycle for mobile devices

What the JD emphasized

  • autonomous systems
  • autonomous and semi-autonomous agents
  • AI-native infrastructure
  • agentic skills

Other signals

  • AI-driven tools and infrastructure
  • autonomous systems
  • agents and infrastructure
  • AI-driven testing
  • autonomous and semi-autonomous agents
  • AI-native infrastructure
  • agentic skills