AI Agent Engineer - Build Production-Ready Voice Agents

Simple AI Lab Company; San Francisco, Northern (CA, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary & meaningful equity

Employee-friendly equity terms

SF office

Health, dental & vision insurance

Free lunch & dinner at the office

Late night Ubers

Regular team events & offsites

Job summary

Simple AI is building state-of-the-art voice AI agents for enterprise. We are hiring an AI Agent Engineer to work directly with customers and turn Simple’s voice AI platform into production-ready agents for each business.

This role is highly technical and customer-facing, spanning pre-sales to post-sales: building demos for prospective customers, understanding customer workflows, deploying agents, debugging edge cases, improving performance, and turning feedback into product improvements.

Qualifications

• 1-3 years of relevant work experience.
• Strong problem-solving skills and enthusiasm for addressing technical challenges.
• A customer-first mindset with strong communication skills and interest in product design and prioritization.
• Self-motivated and able to work independently.
• Passion about learning and keeping up with latest AI advancements.

Responsibilities

• Build custom demos for prospective customers.
• Understand customer workflows and deploy agents.
• Debug edge cases and improve performance.
• Turn customer feedback into product improvements.

Skills

Problem solving

Customer focus

Communication

Self-motivated

Learning mindset

Tools

TypeScript

React

Python

Ruby on Rails

PostgreSQL

AWS

Job description

Simple AI is building state-of-the-art voice AI agents for enterprise. We are hiring an AI Agent Engineer to work directly with customers and turn Simple’s voice AI platform into production-ready agents for each business.

This role is highly technical and customer-facing, spanning pre-sales to post-sales: building demos for prospective customers, understanding customer workflows, deploying agents, debugging edge cases, improving performance, and turning feedback into product improvements.