Frontier AI Engineer - Cloud Conversational Systems

Google; Chicago (IL); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

Paid time off

Job summary

Google Cloud Applied AI is seeking a Forward Deployed Engineer III to lead the delivery of conversational AI pilots at customer sites, translating rapid prototypes into production-ready agentic workflows. You will own end-to-end engineering, from architecting flows to integrating with customers’ live infrastructure and security perimeters.

This role requires deep software engineering, ML ops, and cloud expertise, with frequent travel up to 50%.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of software development in Python or similar languages.
• Experience architecting AI systems on cloud platforms (e.g., GCP).
• Experience deploying resources via Terraform or similar tools to automate 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 conversational AI and CX applications, turning prototypes into production-grade workflows.
• Architect and code conversational flows optimized for connecting AI products with customers’ live infrastructure and security perimeters.
• Build Eval pipelines and observability frameworks to optimize agent workloads with attention to latency and security.
• Identify reusable modules from field patterns to support Engineering teams.
• Co-build with customer teams to ensure best practices and long-term adoption.

Skills

Python

Terraform

Cloud architecture

AI systems

Full-stack integration

Education

Bachelor’s degree

Tools

Terraform

Job description

Google Cloud Applied AI is seeking a Forward Deployed Engineer III to lead the delivery of conversational AI pilots at customer sites, translating rapid prototypes into production-ready agentic workflows. You will own end-to-end engineering, from architecting flows to integrating with customers’ live infrastructure and security perimeters.

This role requires deep software engineering, ML ops, and cloud expertise, with frequent travel up to 50%.