Forward-Deployed GenAI Engineer, Cloud AI

GOOGLE

City Of London

On-site

GBP 120,000 - 180,000

Full time

14 days+

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Job summary

Google Cloud is seeking a Forward Deployed Engineer to embed with customers and bridge frontier AI products with production-grade reality. You will code, debug, and jointly ship bespoke agentic solutions directly within the customer environment.

This high-agency role involves solving integration challenges, data readiness, and state-management issues while collaborating with DeepMind engineers and the Go-To-Market team to influence product roadmaps and deliver measurable ROI across enterprise

Qualifications

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience with software development using Python or similar coding languages.
Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
Experience taking production-grade AI-driven solutions from conception to launch, and architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
Experience leading technical discovery sessions with customers.
Ability to communicate in French or German fluently as this is a customer-facing role that requires interactions in French or German with local stakeholders.

Responsibilities

Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) 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 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 end-user adoption.