Forward Deployed Engineer III, Generative AI, Google Cloud
Teknik, data och digitalt · Mjukvaru- och webbutveckling · Mjukvaruutveckling · Maskininlärning · Molnteknik
I korthet
As a GenAI Forward Deployed Engineer at Google Cloud, you will embed with customers to build and deploy production-grade AI solutions. This role focuses on coding, debugging, and integrating complex agentic systems, acting as a crucial link between advanced AI products and customer environments. You will leverage Google's AI portfolio to solve business problems and provide feedback for future product development.
Ansvarsområden
- Serve as a developer for complex AI applications, transitioning from prototypes to production-grade agentic workflows that drive measurable ROI.
- Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Krav
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience with software development using Python or similar coding languages.
- Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
- Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
- Experience leading technical discovery sessions.
Önskade kvalifikationer
- Master’s or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Förmåner
- 15% bonus target
- Equity
- Benefits package
#Generative AI#Google Cloud#Software Development#AI#Machine Learning#Cloud Engineering