AI Engineer (Brilliant Harvest)

Location: Canada; remote-first role

Company

hirify.global is developing the Brilliant Harvest platform, applying AI to workflows for equipment dealers, farmers, and contractors.

What you will do

• Design, build, and ship production AI agents that plan, use tools, and complete multi-step tasks.
• Implement agent orchestration, memory, MCP integrations, guardrails, and human-in-the-loop checkpoints.
• Develop and maintain RAG pipelines, LLM integrations, and document ingestion components covering parsing, chunking, enrichment, and indexing.
• Evaluate agent and answer quality using task success, tool-call accuracy, cost, latency, test sets, automated checks, and LLM-as-judge methods.
• Investigate issues across tool calls, retrieval, and ingestion, and prototype new LLMs, frameworks, and tooling.
• Collaborate with Product, Data, Design, and QA through design reviews, code reviews, estimation, and delivery.

Requirements

• 3+ years of professional software engineering or data science experience, including at least 1 year building AI/ML or LLM-powered applications.
• Practical experience building LLM agents with tool calling, multi-step orchestration, and agent frameworks or protocols such as MCP.
• Hands-on experience with generative AI and LLMs, including RAG, embeddings, vector search, or document ingestion, ideally with a production feature.
• Strong Python proficiency and working experience with TypeScript, C#/.NET, or another modern backend language.
• Working knowledge of API design, microservices, and cloud infrastructure.
• Clear communication, early escalation of blockers, constructive feedback, clean tested code, coding standards, and CI/CD practices.

Nice to have

• Familiarity with React, React Native, or another modern frontend framework and AI-powered backend integration.
• Prompt engineering and AI-first development tooling experience, such as Claude Code.
• Exposure to LLM and agent evaluation methods, including test sets, LLM-as-judge, or human review.
• Startup experience.
• Experience in agriculture, heavy equipment, or dealership domains.
• Experience with typed decision models such as TypeSafe's Jev.

Culture & Benefits

• Remote-first work with a flexible environment.
• Hands-on mentorship from the Lead AI Engineer and opportunities to take on larger, more ambiguous problems.
• Collaborative culture focused on growth, learning, knowledge sharing, and impact.
• Competitive compensation, ESOP, and benefits.