AI Agent Engineer

Role overview

What you'll do

• Ship agent capabilities from data and tools through reasoning and execution to the media-buyer interface.
• Use tools such as Codex, Claude Code, and Cursor in the development workflow and remain accountable for shipped software.
• Decide which agent actions are autonomous and which should be escalated to a human, using risk and confidence.
• Set boundaries between LLM reasoning and deterministic software execution.
• Build tools, retrieval, memory, orchestration, guardrails, and approval flows for reliable agents.
• Handle incomplete context, tool failures, and workflows that pause and resume.
• Convert customer workflows and production failures into evaluations and regression tests; inspect traces and improve prompts and context.
• Join customer calls, review transcripts, and turn feedback and ambiguous problems into shipped product.

What you'll bring

• Track record building and shipping production software used by customers; specific years of experience are not the focus.
• Strong software engineering experience with backend or full-stack depth, including system design, APIs, data models, testing, debugging, and production operations.
• Hands-on LLM or agent-building experience from work, open source, or a substantial personal project, with ability to discuss behavior and limitations.
• Comfort across the stack, with depth in at least one area and willingness to work in less familiar areas.
• Experience with or strong interest in daily use of AI coding tools, plus the technical judgment to review and reject weak output.
• Curiosity and judgment about where AI belongs and where conventional software is the better choice.
• Able to make reasoned decisions, ship, and iterate quickly while maintaining quality and maintainability.

Technology

• The stack includes Python, FastAPI, LangGraph, LangChain, TypeScript, Vue, Nuxt, Java, Spring Boot, PostgreSQL, pgvector, Redis, NATS, and AWS.
• The role uses AI coding tools such as Codex, Claude Code, and Cursor.
• Prior experience with every listed framework or agent concept is not required; the company expects engineers to learn on the job.

Not required

• An AI research background or experience training foundation models is not required.
• Prior experience with every agent framework or concept is not required.
• Prior advertising or Amazon DSP experience is not required.

Bonus experience

Working environment

Compensation and equity

• Base salary is $110,000 to $200,000 depending on experience level.
• The company offers equity and says top performers may receive additional equity grants.

Workplace

• The team works together in downtown Toronto; makers such as engineers may choose to work elsewhere on Wednesdays.

Benefits

• Benefits include catered daily lunch, snacks, Apple equipment, and comprehensive health and dental coverage.