Forward Deployed Engineer (FDE) - Gen AI / Applied AI

Forward Deployed Engineer (FDE) – Gen AI / Applied AI

Location: Remote – California
Work Hours: PST
Priority: Immediate – Candidates needed today/tomorrow
Travel: Up to 50% may be required for Applied AI roles

Job Summary

We are seeking a highly experienced Forward Deployed Engineer (FDE) specializing in Generative AI, Applied AI, and Conversational AI to work directly with enterprise customers and transform AI prototypes into production-grade solutions.

This is a hands-on engineering role requiring strong software development, AI architecture, cloud infrastructure, and customer-facing technical delivery experience. The FDE will build, debug, deploy, and optimize agentic AI and conversational AI solutions within complex enterprise environments.

Key Responsibilities

• Build and deploy production-grade Generative AI and Agentic AI applications.
• Transform rapid AI prototypes into scalable, secure, production-ready solutions.
• Develop multi-agent workflows, MCP servers, conversational applications, and AI-driven customer solutions.
• Architect and implement integrations between Google Cloud AI products and enterprise infrastructure, including APIs, legacy systems, data silos, and security environments.
• Work with Gemini-powered Conversational AI, Customer Engagement Suite (CES), and Contact Center AI (CCAI).
• Build evaluation pipelines and observability frameworks to measure and optimize accuracy, safety, latency, reasoning, and tool selection.
• Develop data pipelines and RAG architectures using structured and unstructured enterprise data.
• Integrate AI agents with enterprise knowledge bases and vector databases.
• Troubleshoot agent behavior, integrations, networking, and production issues.
• Identify recurring technical challenges and develop reusable solutions, modules, and implementation patterns.
• Work directly with customer engineering teams to implement best practices and accelerate production adoption.
• Lead technical discovery sessions, architecture discussions, and customer-facing solution workshops.
• Drive AI projects from proof of concept through production deployment.
• Support high-impact enterprise deployments and troubleshoot live, high-traffic systems when required.

Required Skills & Experience

• Bachelor’s degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.
• 5+ years of professional software development experience, with strong proficiency in Python or similar programming languages.
• Hands-on experience architecting and deploying AI systems on cloud platforms, particularly Google Cloud / Google Cloud Platform.
• Production experience building and deploying AI-driven solutions for enterprise customers.
• Hands-on experience with Google Conversational AI products, including:
  • Gemini-powered Conversational Agents / CX
  • Customer Engagement Suite (CES)
  • Contact Center AI (CCAI)
• Experience building RAG solutions, including vector databases, embeddings, enterprise knowledge bases, and structured/unstructured data pipelines.
• Experience developing full-stack applications integrated with enterprise IT environments.
• Experience with Terraform or similar infrastructure-as-code tools for deploying agents, functions, networking, and cloud resources.
• Strong understanding of Agentic AI, Conversational AI, and multi-agent architectures.
• Experience with production AI architecture, software engineering, cloud infrastructure, and deployment.

Preferred Skills

• Experience with LangGraph, CrewAI, Google ADK, or similar agent frameworks.
• Experience implementing ReAct, self-reflection, hierarchical delegation, and other advanced agent patterns.
• Experience with MCP servers and agent/tool orchestration.
• Strong understanding of AI evaluation, observability, tracing, and LLM-native metrics.
• Experience optimizing:
  • Token usage
  • Latency
  • Cost per request
  • Agent state management
  • Tool selection
  • Reasoning loops
• Experience debugging complex agent workflows across multiple microservices.
• Experience optimizing RAG chunking and retrieval to reduce hallucinations.
• Experience with Dialogflow CX, CX Agent Studio, SCRAPI, Agent Assist, and CCaaS.
• Experience troubleshooting live, high-traffic production systems.
• Telecom architecture experience, including telecom APIs, user authentication (UA), and enterprise business architectures (BAA).
• Master’s or PhD in AI, Computer Science, or related field.
• Ability to travel up to 50% for customer engagements.

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