AI Engineer
Quick Summary
1. A Loom video (2-3 minutes) Tell us who you are, what you're working on or have recently built, and how AI is a core part of how you work. Don't script it. We want to see how you think out loud. 2.
This role sits at the intersection of AI engineering and application development. You’ll build customer-facing features from scratch, while also helping us integrate and scale the AI infrastructure that power them. You're deeply fluent in TypeScript and React, strong enough on the backend to own a feature end-to-end, and have meaningful experience building AI applications. You craft fast, polished, reliable software and you're drawn to problems that are genuinely unsolved.
We're looking for full stack engineers and those who lean more towards frontend.
Nice to Have
~1 min readTell us who you are, what you're working on or have recently built, and how AI is a core part of how you work. Don't script it. We want to see how you think out loud.
A link, a side project, a campaign. Anything that shows what you're capable of making. One strong example beats ten weak ones.
- Why Durable
- Where are you located
- What are your salary expectations
We are a Vancouver-based company and candidates need to be based in Canada. Remote is fine - you can expect travel to Vancouver once per quarter (minimum) to work in-office with the team.
Compensation is $180,000–$225,000 CAD base plus equity, for Vancouver-based candidates. Actual salary takes experience, location, and other factors into account.
Languages: Typescript, SQL, Bash, HTML5, CSS3, Python
Frameworks/Libraries: React, NextJS, React Query, React Native, Expo, TailwindCSS, RadixUI, DrizzleORM, trpc, NodeJS, Bun, WebRTC, PyTorch
Tooling: Turborepo, ESLint, Prettier, NPM/PNPM, Git, AI codegen
Databases: Postgres (including PGVector and JSON datatype), Object stores
Infrastructure: Docker, Cloudflare (Workers, Durable Objects, Pages, DNS, CDN), Vercel, Inngest, Render, Trigger.dev, Datadog, Together.ai, LangSmith, Hugging Face, Replicate, Langfuse
AI engineering: Large Language Models, Multi-Modal Models, Image Generation, In-painting, Voice Models
AI concepts (learn over time): Basic Prompting, Chain of Thought prompting, N-shot prompting, Prompting reasoning models, Tool calling, Preprocessing unstructured data, ReAct, Agent basics, Advanced agentic patterns, Evals, Memory, Generative UI, Streaming, Real-time, Multi-agent systems, Guardrails, Citations, Vector databases, RAG, Text embeddings, Knowledge graphs, Query routing, Synthetic data, Fine-tuning, RLHF, Diffusion Models, MCP, Computer use, Using/Serving Multi-modal OSS models
Listing Details
- Posted
- March 27, 2026
- First seen
- March 26, 2026
- Last seen
- April 14, 2026
Posting Health
- Days active
- 19
- Repost count
- 0
- Trust Level
- 52%
- Scored at
- April 14, 2026
Signal breakdown
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