Full Stack Engineer, AI

About Durable:

Our mission at Durable is to make owning a business easier than having a job.

Durable builds AI that does the work for you. Our goal is to own the DIFY (Do It For You) small business category.

What is DIFY? It is a new category of technology that is faster and more cost effective than a human, and much easier to use than software. It is an AI first approach to solving customer problems.

You don't need to learn new software. You don't need to read help docs. You don't need to learn how to prompt. You provide business context and feedback, and the work is done for you.

We believe in a world where everyone is a business owner. Whether it's a full-time, part-time, or side hustle - we want to make it frictionless to start and operate a business. Since launching in late 2022, over 5 million websites have been built with our AI powered website builder. We are generating significant revenue, well-funded by Silicon Valley investors, and growing extremely fast.

Our vision is much bigger, and we're looking for incredible people to join our team and make an impact.

What You’ll Do:

This role sits at the intersection of product engineering and AI infrastructure. You’ll build customer-facing features from scratch, while also helping us integrate and scale the AI systems that power them.

Key Responsibilities:

• Build full-stack, AI based features within our stack (see below). 
• Design and implement end-to-end AI workflows and agents applying techniques like Retrieval Augmented Generation (RAG), Memory, tool calling, reasoning and other techniques.
• Collaborate with product, design, and AI teams to integrate cutting-edge model capabilities, shape product direction, and prototype new ideas.
• Stay at the forefront of AI/ML innovation, push the collective knowledge of the team and turn insights into advantages for customers.

What you'll bring: 

• 2+ years of professional experience building production-grade software
• High fluency with React, NextJS, TypeScript, and engineering best practices
• Strong backend experience scaling apps and services.
• Functional understanding of concepts in applied AI like CoT, RAG, Memory, MCP and more.
• Bonus: Experience shipping multi-modal LLM workflows or agentic apps to production.

Why Join Us?

At Durable, we’re committed to creating an environment where you can thrive. Here’s what you can look forward to:

• Vancouver HQ: Based in Vancouver? Our Gastown HQ comes with jaw-dropping North Shore views. Many teammates come in on Mondays and Thursdays, but WFH is always an option when you need it.
• Comprehensive benefits: Health and dental coverage to support your well-being.
• Home office stipend: Receive a stipend to create a comfortable and productive workspace.
• Professional development: We support your growth with opportunities like conferences, courses, and speaking engagements.
• Team events: Connect with your colleagues through retreats and team-building activities.
• Equipment: Start strong with a company-provided laptop and the tools you need to succeed.
• Commitment to engineering excellence: We care deeply about our craft and build using the most AI-native stack and tools available

Location:

Ideal candidates are based in Vancouver. We may consider those based remotely in Canada on a case-by-case basis. 

Compensation:

Base salary range is $180,000-$225,000 CAD, plus equity. This range is relevant to candidates located in Vancouver, Canada. Actual compensation will be based on a combination of factors including location, experience, and skill level.

Recruitment process:

This is our typical recruitment process. It may vary a bit but generally this is what you can expect to take place over the span of several weeks. The behavioural, technical, and group portions are often completed at the same time at our office.

• Recruiter screen (Online, 15-20mins)
• Hiring Manager screen (Online, 15-20mins)
• Behavioural (On-site, 30mins)
• Technical Interview (On-site, 90mins)
• Group Chat (Online or On-site, 25mins)
• References + Offer

Tech stack: 

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