About The Position

The Capgemini team offers extensive career opportunities and provides mentoring and coaching for teammates. This role is an experienced professional with a strong background in software development. 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. 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. Deep understanding of software engineering, Machine Learning Operations, and cloud infrastructure. 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.

Requirements

  • 10 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.

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

Benefits

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
  • Company paid holidays
  • Personal Days
  • Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility
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