Forward Deployed Engineer, Google Cloud Consulting
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Minimum qualifications:
- 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 AI solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
- Experience building pipelines for structured and unstructured data using both vector databases and retrieval augmented generation like architectures to power enterprise AI solutions.
- Experience leading technical discovery sessions with customers.
- Experience architecting AI systems on cloud platforms (e.g., GCP).
Preferred qualifications:
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, Agent Development Kit (ADK)) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
- Experience in a post-sales or technical consulting delivery function.
- Knowledge of large language model native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the job
As a Forward Deployed Engineer (FDE) in the Google Cloud Consulting organization, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.
Ireland: €122000 - €126000 (EUR) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable Return on Investment (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 as part of an expert team.
- 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 for the Engineering teams.
- Co-build with pre-sales and product teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
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