3 days ago
Singapore, SingaporeStaff+
Responsibilities
- Architect and develop reusable generative media solutions, vertical-specific templates, and technical assets such as code repositories and cookbooks.
- Develop complex AI applications and transition prototypes into production-grade agentic workflows, including multi-agent systems and MCP servers.
- Architect and code integrations between Google AI products and customer infrastructure, including APIs, legacy data silos, and security perimeters.
- Build evaluation pipelines and observability frameworks for agentic systems that measure accuracy, safety, and latency.
- Identify repeatable customer patterns and friction points and convert them into reusable modules or product feature requests for engineering teams.
- Embed with strategic accounts to provide white-glove deployment and turn customer insights into product roadmap feedback.
Requirements
- Bachelor’s degree in engineering, computer science, a related field, or equivalent practical experience.
- At least 8 years of experience in software development or machine learning.
- At least 3 years of experience building with or fine-tuning generative AI models for image, video, or audio generation.
- Experience taking production-grade AI-driven solutions from conception to launch for customers and architecting AI systems on cloud platforms such as GCP.
- Experience building structured and unstructured data pipelines using vector databases and RAG-like architectures.
- Experience with software development in one or more programming languages, such as Python, for generative media.
- Experience with generative model architectures such as Diffusion Models and Vision Transformers.
- Experience building applications or proofs of concept with Python and ML libraries such as PyTorch, TensorFlow, and JAX.
- Experience implementing multi-agent systems with frameworks such as LangGraph, CrewAI, and ADK and patterns such as ReAct, self-reflection, and hierarchical delegation.
- Experience managing go-to-market strategies for AI technologies.
- Knowledge of LLM-native metrics such as tokens per second and cost per request, and techniques for optimizing state management and granular tracing.
- A master’s degree or PhD in AI, computer science, or a related technical field is preferred.
Tech Stack
Categories
Forward Deployed
About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.