Hybrid Forward-Deployed AI Engineer

Capgemini; Atlanta (GA); Hybrid; USD 109,000 - 197,000; Full time

Benefits offered by this job

Paid time off

Health coverage

Retirement plans

Life and disability insurance

Employee assistance programs

Job summary

Capgemini seeks a Lead Software Engineer to drive AI-enabled solutions across hybrid U.S. locations including Atlanta, Chicago, Dallas, and Nashville.

You will lead end-to-end development of agentic AI applications, design multi-agent workflows, and integrate AI with enterprise systems while aligning with security, reliability, and scalability goals. You will work with cloud-native architectures on GCP, apply Terraform for deployments, and advance MLOps practices across production environments.

Qualifications

• Experience in software development with Python.
• Strong GCP and cloud-native architecture.
• Hands-on with Terraform.
• Production AI/ML deployments.
• Full-stack apps integrated with enterprise systems.
• APIs, microservices, security and integrations.
• MLOps, monitoring and observability.

Responsibilities

• Lead development and deployment of Conversational AI and Agentic AI solutions.
• Design multi-agent systems and AI-powered CX solutions.
• Build integrations with enterprise environments via APIs and data platforms.
• Develop evaluation pipelines and observability frameworks.
• Troubleshoot agent behavior and optimize performance.
• Use IaC (Terraform) to automate cloud deployments.
• Partner with customer engineers to drive best practices.
• Identify recurring patterns and contribute reusable frameworks.

Skills

Python

GCP

Terraform

AI/ML in prod

APIs & microservices

Full-stack integration

Security & networking

MLOps

Education

Master's or PhD in CS/AI/ML

Tools

Terraform

Job description

Capgemini seeks a Lead Software Engineer to drive AI-enabled solutions across hybrid U.S. locations including Atlanta, Chicago, Dallas, and Nashville.

You will lead end-to-end development of agentic AI applications, design multi-agent workflows, and integrate AI with enterprise systems while aligning with security, reliability, and scalability goals. You will work with cloud-native architectures on GCP, apply Terraform for deployments, and advance MLOps practices across production environments.