US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Design, write, and deploy production-grade code for multi-agent workflows, tool-use orchestration engines, and dynamic decision-making pipelines.
Deploy AI frameworks and tools, to enable velocity in product development and scalability of agentic applications that require high-precision and safe execution under complex real-world conditions.
Build robust, high-throughput model serving pipelines and real-time execution environments optimized for latency, reliability, and scale.
Integrate continuous, data-driven feedback loops into AI development methodologies. Construct automated testing, continuous evaluation, and observability frameworks to assess agent coverage, monitor regressions, and safeguard product quality across end-to-end workflows.
Adopt and integrate distributed tracing, data lineage architectures, and telemetry (e.g., OpenTelemetry) into high-volume generative AI data pipelines.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in Java.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 1 year of experience with GenAI techniques (e.g., LLMs,
- Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience in machine learning infrastructure.
Preferred qualifications
Master's degree or PhD in Computer Science, or a related technical field.
1 year experience in machine learning, generative AI and AI algorithms.
1 year of experience in a technical leadership role.
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in Java.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 1 year of experience with GenAI techniques (e.g., LLMs,
- Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Experience in machine learning infrastructure.
