About this role
( Any 1 Certification is mandatory )
"1- CPS Certifications- Candidate must hold both Cloud Partner Specialist (CPS) certifications.
2-Atleast one additional Google Cloud Professional certificate.
3- Candidates must be currently deployed on an active GE project or assigned to an upcoming GE project starting within next 2 months (spaces permitting)"
Job Title- FDE - Gen AI
Location: Remote (work timing PST)
• 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 an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. This role is designed for high-agency engineers with a founder’s mindset.
• You will address blockers 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.
Job 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 (Gemini-powered CX, Customer Engagement Suite, and Contact Center AI) 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 rigorous 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 customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
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 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 taking production-grade AI-driven solutions from conception to launch for customers.
• Experience leading technical discovery sessions with customers.
• Hands-on experience implementing and customizing Google’s Conversational AI product suite, including Conversational Agents (Gemini-powered CX), Customer Engagement Suite (CES), and Contact Center AI (CCAI).
Preferred Qualifications:
• 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.
• Additional deployment readiness criteria (Google RFI benchmark)
• Conversational AI & Agentic Depth: Production-grade experience architecting voice and agentic systems across the Google Enterprise CX ecosystem (Dialogflow CX, CX Agent Studio, SCRAPI, Agent Assist, CCaaS).
• Vetted Technical Rigor: Formally assessed, top-decile engineering talent (e.g., Google AI/FDE Bootcamp certification or verified 80%+ benchmark assessments).
• Telecom Architecture Fluency: Demonstrated domain depth with telecom APIs, user authentication (UA), and enterprise business architectures (BAA).
• Autonomous Delivery & Multiplier Impact: Senior "tiger team" talent capable of driving execution independently while actively upskilling co-delivery partner teams.
Role: FDE - Applied AI
Location: Remote (work timing PST)
• As a Forward Deployed Engineer (FDE) in Applied AI, you are the "Agent Engineer" and the primary driver for our customers' most critical AI initiatives.
• You take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from "Art of the Possible" to real-world business value and scalable, secure AI systems.
• This is a high-travel, high-impact role focused on leading technical delivery for Conversational AI pilots and establishing the first Customer User Journeys (CUJs) for our largest customers at their sites.
• This role requires a deep understanding of software engineering, Machine Learning Operations, and cloud infrastructure.
Job Responsibilities:
• Serve as the lead developer for complex Conversational AI and CX applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
• Architect and code conversational flows that are not just functional but optimized for the "connective tissue" between Google’s Conversational AI products (Gemini-powered Conversational Agents/CX, Customer Engagement Suite, and Contact Center AI) and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation (Eval) pipelines and observability frameworks to optimize complex agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
• Identify repeatable field patterns and technical "friction points" in Google’s AAI stack, converting them into reusable modules or product feature requests for Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
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 architecting AI systems on cloud platforms (e.g., GCP).
• Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
• Hands-on experience implementing and customizing Google’s Conversational AI product suite, including Conversational Agents (Gemini-powered CX), Customer Engagement Suite (CES), and Contact Center AI (CCAI).
Preferred Qualifications:
• Master’s or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
• Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
• Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
• Track record of troubleshooting live, high-traffic systems during critical windows.
• Ability to travel up to 50% of the time.
• Additional deployment readiness criteria (Google RFI benchmark)
• Conversational AI & Agentic Depth: Production-grade experience architecting voice and agentic systems across the Google Enterprise CX ecosystem (Dialogflow CX, CX Agent Studio, SCRAPI, Agent Assist, CCaaS).
• Vetted Technical Rigor: Formally assessed, top-decile engineering talent (e.g., Google AI/FDE Bootcamp certification or verified 80%+ benchmark assessments).
• Telecom Architecture Fluency: Demonstrated domain depth with telecom APIs, user authentication (UA), and enterprise business architectures (BAA).
• Autonomous Delivery & Multiplier Impact: Senior "tiger team" talent capable of driving execution independently while actively upskilling co-delivery partner teams.