Full Stack Engineer (AI Products)

Artsloungenyc; Calgary; On-site; CAD 90,000 - 150,000; Full time

Job summary

Precision AI Inc. in Calgary is hiring a full-time Full Stack Engineer to build features that bring AI to farmers and operators. You will work on either the internal AI platform or external-facing AI products on a core software team alongside an Infrastructure & DevOps Engineer.

You’ll contribute to LLM-based tools, prompt engineering, and multi-step workflows using React on the frontend and Node/TypeScript on the backend, with deployment alongside DevOps for scalable, observable features.

Qualifications

• Experience with LLMs or agent frameworks (LangChain, LangGraph, CrewAI, etc.).
• Familiarity with prompt engineering, evaluation, or monitoring of AI features.
• Python familiarity as our tooling touches it.
• Experience with cloud platforms (AWS) and Docker.
• Exposure to agtech, robotics, autonomous systems, or developer platforms.
• Open-source contributions that show ownership.

Responsibilities

• Design and build full stack features across our web frontend (React) and backend (Node/TypeScript, Fastify, Prisma).
• Integrate LLM and agent frameworks into product features – tool use, multi-step workflows, streaming responses.
• Turn rough requirements into working, shipped features, iterating quickly based on feedback.
• Take features from development through staging to production; keep them reliable and observable.
• Respond to issues, debug problems, and improve the system; collaborate with Infra/DevOps for smooth deployments.

Skills

LLMs / agent frameworks

Prompt engineering

Python

Cloud (AWS)

Docker

Agtech exposure

Open-source contributions

Tools

React

Node.js / TypeScript

Fastify

Prisma

LangGraph

Job description

Precision AI Inc.is hiring a full-time Full Stack Engineer to help build products that put AI into the hands of farmers and agricultural operators. Located in Calgary, Alberta, the engineer will build and ship real features that real users can depend on. This role sits alongside their Infrastructure & DevOps Engineer on the core software team. You’ll contribute to either our internal AI platform (the Velocity Engine) or our external-facing AI products, depending on team priorities.

Learn AI Tools

“Precision AI is on a mission to transform agriculture with cutting-edge drone technology. Our aerial spraying systems help farmers target weeds with surgical precision, reducing chemical use and increasing yields. We’re a fast-moving, impact-driven team looking for people who want to help build the future of farming.”

Applications are open until filled. All qualified applicants will receive consideration for employment without discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other status protected by law.

Applicants should have the following qualifications:

• Any hands-on experience with LLMs or agent frameworks (LangChain, LangGraph, CrewAI, etc.),even side projects or prototypes.
• Familiarity with prompt engineering, evaluation, or monitoring of AI features.
• Python familiarity (some of our tooling touches it).
• Experience with cloud platforms (AWS preferred) and Docker.
• Exposure to agtech, robotics, autonomous systems, or developer platforms.
• Open-source contributions that show ownership.

Applicants will be required to do the following duties:

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Build The Product

• Design and build full stack features across our web frontend (React) and backend (Node/TypeScript, Fastify, Prisma). Build a Website
• Integrate LLM and agent frameworks (LangGraph and similar) into product features – tool use, multi-step workflows, streaming responses.
• Turn rough requirements into working, shipped features, iterating quickly based on feedback.

Ship & Operate

• Take features from development through staging to production; keep them reliable and observable.
• Respond to issues, debug problems (including the non-deterministic quirks of LLM-driven features), and improve the system as you go.
• Work with the Infrastructure & DevOps Engineer to keep deployments smooth and scalable.
• Work closely with product and AI/ML teammates on what to build and how it should behave.
• Add tests, monitoring, and evaluation for the features you own so we can trust them in production.