Job Posting Title
AI/ML Engineer
Location: Toronto, CA (Remote)
What you'll do
- Build enterprise-grade AI agents: As an Agent Engineer, you will be responsible for partnering directly with our CX team to build and ship AI agents that handle thousands of customer conversations a day.
What you’ll bring
- 3+ years experience in hands-on software development of highly technical products.
- Past experience in Software Development or other similar hands-on development roles at or above the level of Senior Software Engineer.
- Experience crafting and tailoring messages for potential customers, including executives.
- Degree in Computer Science or related field, or equivalent professional experience.
Skill Requirements:
- AI-related experience (experience developing code-based AI agents such as conversational AI agents a plus).
- Experience with React, Typescript, and Go.
- Experience interfacing with end customers to influence software development.
- Engineers working on building AI agents should be self-sufficient at a senior level, familiar with software development lifecycles, capable of writing code independently, including building components, integrating with APIs, and testing/deployment.
- The AI agent is built programmatically using code, involving extensive coding workflows for setup, permissions, version control, development, testing, and deployment.
- Strong experience in ReactJS and Typescript, comfortable with Git and other engineering workflows.
- Understanding of LLMs and API integrations in Typescript.
- Deep understanding of React development lifecycle and component architecture to develop against the Agent SDK, which has distinctions from React.
Most engineers should know:
- React (Intermediate to Advanced)
- Typescript (Intermediate to Advanced)
- LLM/prompt engineering basics
- Git/version control
- Terminal usage
Typical AI Engineer Responsibilities:
- Build the agent from scratch based on product requirements.
- Develop, test various scenarios including knowledge retrieval and support journeys, and write simulation tests.
- Interface directly with clients to ensure the agent meets their needs and connects to necessary APIs/databases.
- Review live conversations and client feedback, identify negative interactions, create issues, and implement improvements.
- Regularly evaluate metrics and enhance the agent's performance in steady state.