AI Engineer

AltaML

. Design, build, and ship production AI agents that plan, use tools, and complete multi-step tasks across the Brilliant Harvest platform .

Posted 11/5/2026full-timeRemote • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining AI agents, with a strong focus on LLM integrations, tool orchestration, and evaluation methodologies. Proficient in Python and familiar with modern backend and frontend frameworks to deliver high-quality, production-ready features.

Highest-signal resume keywords

AI/ML Application DevelopmentLLM Agent FrameworksPython ProgrammingAPI DesignCollaborative Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Agent DesignLLM IntegrationTool OrchestrationDocument IngestionEvaluation MethodologiesPythonTypeScriptC# (.NET)MicroservicesPrompt Engineering

Soft Skills

Collaborative ApproachMentoringClear CommunicationFeedback Reception

Tools & Technologies

CI/CD PracticesAI-First Development ToolingReactReact NativeCloud Infrastructure

Industry Keywords

Agriculture DomainHeavy EquipmentDealership DomainStartup Environment

Tech Stack

Tools & technologies

CloudMicroservicesPythonReactReact NativeTypeScript.NET

About the role

Key responsibilities & impact

Design, build, and ship production AI agents that plan, use tools, and complete multi-step tasks across the Brilliant Harvest platform
Implement agent orchestration, memory, tool integrations, guardrails, and human-in-the-loop checkpoints for high-stakes actions
Evaluate agents end to end, measuring task success, tool-call accuracy, cost, and latency
Design, develop, test, document, and maintain production features for the AI platform, including RAG pipelines and LLM integrations
Build and improve document ingestion pipelines covering parsing, chunking, enrichment, and indexing
Investigate agent and answer-quality issues across tool calls, retrieval, and ingestion to identify root causes
Build and maintain evaluation datasets and automated checks, including LLM-as-judge
Prototype new LLMs, agent frameworks, and tooling, and share findings informing model and vendor decisions
Participate in brainstorming, design reviews, and code reviews
Write clean, well-tested code and follow coding standards and CI/CD practices
Use AI-first development workflows while critically reviewing generated output
Analyze feature requirements, break work into tasks, and provide effort estimates
Collaborate with Product, Data, Design, and QA teams to deliver roadmap-aligned features
Provide technical feasibility input on AI feature UI/UX designs and integrate them with backend systems
Communicate progress, blockers, and technical tradeoffs to technical and non-technical teammates
Share knowledge through code reviews, pairing, documentation, and demos; help junior engineers get up to speed
Mentor teammates and guide architectural decisions

Requirements

What you’ll need

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, including tool calling, multi-step orchestration, and agent frameworks or protocols such as MCP
Hands-on experience with generative AI and LLMs, such as RAG, embeddings and vector search, or document ingestion, ideally with at least one feature in production
Strong proficiency in Python, plus working experience with at least one of: TypeScript, C# (.NET), or another modern backend language
Working knowledge of API design, microservices, and cloud infrastructure
Familiarity with React, React Native, or other modern frontend frameworks, and how they integrate with AI-powered backends, is an asset
Experience with prompt engineering best practices and AI-first development tooling (e.g., Claude Code or similar) is a strong asset
Exposure to evaluation methods for LLM applications and agents, such as test sets, LLM-as-judge, or human review, is an asset
Experience working in a startup environment is an asset
Familiarity with the agriculture, heavy equipment, or dealership domain is a strong asset
Collaborative approach: communicate clearly, raise blockers early, and give and receive feedback constructively

Benefits

Comp & perks

Remote-first role with a flexible work environment
Competitive compensation
ESOP
Benefits
Collaborative culture that values growth, learning, and impact