Applied AI Engineer: Frontline Deployments & Impact

Capgemini; New York (NY); Hybrid; USD 82,000 - 193,000; Full time

Job summary

Capgemini is seeking a Forward Deployed Engineer (FDE) in Applied AI to lead production-grade Conversational AI pilots across client sites. You will transform rapid prototypes into scalable, secure AI solutions, owning end-to-end engineering from concept to deployment.

You will work with cross-functional teams, design robust Conversational AI flows, integrate with enterprise systems, optimize latency, and ensure high-end user adoption.

Qualifications

• Bachelor's degree in Engineering, CS, or related field.
• 5 years of software development experience (Python or similar).
• Experience architecting AI systems on cloud platforms (e.g., GCP).
• Experience deploying resources via Terraform or similar tools.
• Experience building full-stack applications interfacing with enterprise IT.

Responsibilities

• Lead development for Conversational AI and CX apps, moving prototypes to production.
• Architect conversational flows integrated with live infrastructure, APIs, data silos, and security perimeters.
• Build evaluation pipelines and observability for agent workloads, focusing on latency and security.
• Connect agents to enterprise knowledge bases and optimize RAG chunking to reduce hallucinations.
• Lead technical delivery for AI pilots at customer sites and collaborate with customer engineering teams.

Skills

Python

GCP

Terraform

APIs

Full-stack development

Education

Bachelor's degree in Engineering, Computer Science, or related field

Master's degree or PhD in AI/CS

Tools

ReAct framework

Job description

Capgemini is seeking a Forward Deployed Engineer (FDE) in Applied AI to lead production-grade Conversational AI pilots across client sites. You will transform rapid prototypes into scalable, secure AI solutions, owning end-to-end engineering from concept to deployment.

You will work with cross-functional teams, design robust Conversational AI flows, integrate with enterprise systems, optimize latency, and ensure high-end user adoption.