Google's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products handle information at massive scale and extend well beyond web search. We seek engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design, and mobile. As a Forward Deployed Engineer (FDE) in Applied AI, you are the "Agent Engineer" and the primary delivery arm for our customers' most critical AI initiatives. You will transform initial conversational prototypes into production-ready solutions, owning the end-to-end engineering life-cycle. The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise, enabling high adoption and speed to value by building solutions that are quickly deployed. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.
Tasks
- Serve as the delivery lead for conversational AI pilots, taking initial proof-of-value code and refactoring it for production by replacing stubs with secure, real-world integrations.
- Own the delivery of the initial Customer User Journeys (CUJs), ensuring that conversational flows are not just functional, but optimized for top customer and industry priorities.
- Architect and optimize complex agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
- Implement critical infrastructure, including rate limiting, error management, and regional failover strategies; develop monitoring systems and alerting dashboards during "Go-Live" windows to ensure stability as traffic scales.
- Architect security perimeters (VPC, IAM, CMEK) to satisfy CISO requirements and optimize RAG strategies to balance latency, accuracy, and cost.
Requirements
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages (e.g., Python or C++).
- 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
- 1 year of experience with AI/ML infrastructure (e.g., model deployment, model evaluation, model optimization, data processing, or debugging).
- Experience developing and deploying multilingual natural language processing models.
- Master's degree or PhD in Computer Science, AI, Machine Learning, or a related technical field (preferred).
- Expertise in debugging Agent logic (ReAct loops, Chain of Thought) and optimizing tool selection (preferred).
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s Agent Development Kit (ADK)) and complex patterns like ReAct, self-reflection, and hierarchical delegation (preferred).
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations (preferred).
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Das Team
Team members operate at the forefront of AI, collaborating directly with model builders in a fast-paced, collaborative, and impactful environment.