Forward Deployed Engineer (FDE) - Applied AI

Socket.dev; Atlanta (GA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Capgemini is seeking a Forward Deployed Engineer (FDE) in Applied AI to drive customer AI initiatives from prototype to production. You will own end-to-end engineering, moving ideas from Art of the Possible to scalable, secure AI systems while collaborating with cross-functional teams.

This high-travel role focuses on leading technical delivery for Conversational AI pilots and defining Customer User Journeys for major clients at their sites.

Responsibilities

• Lead development for Conversational AI and CX applications
• Architect and code conversational flows integrating with live infrastructure

Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location

Hybrid work from Chicago, Atlanta, Nashville, Dallas, NY

About the job you're considering

At Capgemini, you will collaborate with cross-functional teams to deliver innovative technology solutions that drive business value and enhance client experiences. You will contribute to the design, development, and continuous improvement of scalable, high-quality solutions in a dynamic and collaborative environment.

Role Overview

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 (MLOps)
• Cloud Infrastructure

Key Responsibilities

Conversational AI & Agent Engineering

• 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 and customers' live infrastructure, including APIs, legacy data silos, and security perimeters.

Evaluation, Optimization & Observability

• 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.
• Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.

Platform Integration &