Production AI Engineer - Conversational CX & Automation

Capgemini

Mountain View (CA)

On-site

USD 76,000 - 118,000

Full time

18 hours ago
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Benefits offered by this job

Medical insurance
Dental insurance
Vision insurance
Retirement benefits

Job summary

Tundra Technical Solutions is seeking a Forward Deployed Engineer (FDE) for Applied AI in Mountain View. You will lead production-ready Conversational AI pilots, transforming rapid prototypes into scalable solutions at customer sites.

The role requires deep software engineering, MLOps, and cloud infrastructure expertise, with travel up to 50%. You will drive end-to-end delivery, including secure deployment and integration with enterprise systems.

Qualifications

  • 8 years of experience in software development.
  • Experience architecting AI systems on cloud platforms (GCP).
  • Experience deploying resources via Terraform to automate setup of agents and networking.
  • Experience building enterprise-scale, production-ready AI solutions.

Responsibilities

  • Serve as the lead developer for Conversational AI and CX applications, turning prototypes into production-grade workflows.
  • Architect and code conversational flows optimized for integration with customer live infrastructure and security perimeters.
  • Build high-performance evaluation pipelines and observability for complex agent workloads and low latency.
  • Identify repeatable field patterns and convert them into reusable modules for Engineering teams.
  • Co-build with customer engineers to ensure long-term success and high end-user adoption.

Skills

Python programming
Software development
MLOps
Cloud infrastructure
Agent-based systems
Multi-agent workflows

Education

Bachelor's degree in Engineering/CS or related field

Tools

Terraform
GCP

Job description

Tundra Technical Solutions is seeking a Forward Deployed Engineer (FDE) for Applied AI in Mountain View. You will lead production-ready Conversational AI pilots, transforming rapid prototypes into scalable solutions at customer sites.

The role requires deep software engineering, MLOps, and cloud infrastructure expertise, with travel up to 50%. You will drive end-to-end delivery, including secure deployment and integration with enterprise systems.

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