FDE - Applied AI

Role: FDE - Applied AI

Location: Remote (work timing PST)

Exp: 15+ years

Job description:

• 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., Google Cloud Platform).
• 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, strong on CCaaS).
• 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)
• 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.