Gen AI Engineer

Job Title : Gen AI Engineer 

Location: Remote 

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).

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., Google Cloud Platform).
• 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.