Forward Deployed Engineer, Generative AI, Telecommunications, Google Cloud

Google • Addison, TX

22h

About The Position

As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded
builder who bridges the gap between frontier AI products and production-grade
reality within customers. Unlike traditional advisory roles, you function as a
"builder-consultant," moving beyond high-level architecture to code, debug, and
jointly ship bespoke agentic solutions directly within the customer’s
environment.

You will manage blocker to production including solving the integration
complexities, data readiness issues, and state-management challenges that
prevent AI from reaching enterprise-grade maturity. By embedding with strategic
accounts, you serve a dual purpose: providing "white glove" deployment of
complex AI systems and acting as a critical feedback loop, transforming
real-world field insights into Google Cloud’s future product roadmap.

Your primary responsibility will be to construct rapid prototype Generative AI
applications tailored to Google Cloud customers, catering to a clientele ranging
from early stage startups to prominent, established companies.

You will be a hybrid professional, blending the core competencies of an engineer
with an aptitude for customer engagement and strategic problem-solving. This
will often require you to lead with deep, bespoke implementation as the primary
value proposition, ensuring that our core technology delivers demonstrable value
in the customer's unique operational context.

You will have close collaboration with our product and engineering teams to
eliminate obstacles and shape the future trajectory of our offerings. You will
be adept at disseminating lessons learned to customers and internal Google
teams, translating one-off customer solutions into reusable, scalable assets.

Google Cloud accelerates every organization’s ability to digitally transform its
business and industry. We deliver enterprise-grade solutions that leverage
Google’s cutting-edge technology, and tools that help developers build more
sustainably. Customers in more than 200 countries and territories turn to Google
Cloud as their trusted partner to enable growth and solve their most critical
business problems.

Requirements

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 6 years of experience in Python and relevant machine learning packages (e.g., Keras, HF Transformers).
• Experience in applied AI, with a focus on designing and evaluating systems around foundation models (e.g., prompt engineering, fine-tuning, RAG, orchestrating model interactions with external tools to deliver solutions).
• Experience architecting, deploying, or managing solutions on a cloud platform.

Nice To Haves

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience delivering AI solutions specifically for telecommunications use cases, such as network optimization, churn prediction, or customer experience enhancement.
• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
• Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.

Responsibilities

• Serve as the lead 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.
• Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and technical "friction points" in Google’s AI stack, converting them into reusable modules or product feature requests for the Engineering teams.
• Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level