--- title: 'AI Engineer at Durable' canonical: 'https://feeny.ai/job/ai-engineer-durable-vancouver-z1dwqav039z3' type: 'job' last_seen: '2026-09-16' --- # AI Engineer at Durable - **Company:** Durable - **Location:** Vancouver, Canada - **Posted:** 2026-03-17 - **Last confirmed live:** 2026-09-16 - **Apply:** https://job-boards.greenhouse.io/durable/jobs/5156304008 ## Job description 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. Full stack. You understand applied AI well past the API layer: building systems that stay reliable when the model is unpredictable, writing evals that surface real signal, designing agentic workflows that hold up under production conditions. You've shipped RAG, tool calling, memory, or multi-agent patterns to real users and you know where each one breaks down. Frontend. You notice things other engineers don't. The easing curve that's slightly off. The transition that happens too fast to register. The empty state that was clearly an afterthought. In a product where AI does most of the heavy lifting, the interface is where trust is built or broken — and you hold that line. You've built design systems from the ground up and have a point of view on motion, interaction, and what makes an AI-generated surface feel considered rather than random. ## What we look for - Production-grade React, NextJS, and TypeScript - Strong backend experience: async systems, API design, schema decisions, scaling under real load - For full stack: applied AI in production like RAG, tool calling, memory, multi-agent patterns, and the ability to write evals and reason about whether a system is actually improving - For frontend: design systems, animation and motion, data-fetching patterns (TanStack Query, tRPC), and deep care for browser fundamentals and performance - Familiarity with our infrastructure and AI tooling (Cloudflare Workers/Durable Objects, Postgres + PGVector, LangSmith, Inngest) is a plus What success looks like Features that are fast, reliable, and polished. Architectural and interaction decisions that make the next thing faster to build. You raise the bar for the people working alongside you. Application process Your works speaks louder than your resume. We want to see how you think, what you've made, and how you work with AI. Our application asks for three things: 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. 1. Something you've built or designed A link, a side project, a campaign. Anything that shows what you're capable of making. One strong example beats ten weak ones. 1. A few short questions - Why Durable - Where are you located - What are your salary expectations Fine print 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. 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](http://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 ## About Durable ## Company Overview - **One-liner**: Durable builds an AI platform that turns natural language descriptions into production-ready, self-maintaining software using explainable neurosymbolic AI. - **Entity Type**: Private (VC-funded startup) - **Headquarters**: Louisville, Colorado, United States - **Founded**: 2022 - **Founders**: Nima Keivan (CEO & Co-Founder), Fernando Nobre (CTO) ## Core Business - **Primary industry/industries**: AI-powered software development, enterprise automation, generative AI - **Target customers**: B2B, enterprise teams needing custom integrations, workflows, and automations without heavy engineering overhead - **Mission or purpose statement**: “Transform access to custom software using explainable AI capable of human-level reasoning and dialogue” – democratizing custom software creation for everyone. ## Products & Services - **Durable Platform (core product)**: A SaaS platform that accepts plain‑English problem descriptions, investigates the user’s systems, generates concrete requirements, writes production code, deploys it with one click, and automatically maintains the automations (error detection, API compatibility monitoring, change approval). Integrates with 30+ enterprise tools (Salesforce, Slack, GitHub, Jira, Stripe, etc.). Built on proprietary neurosymbolic AI, not just LLM wrappers. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Total funding – at least $250k non‑dilutive grant from Colorado OEDIT (awarded November 2023); overall VC‑funded (amounts not specified) - **Notable Investors/Partners**: Not named in available data; described as “VC‑funded startup founded by repeat founders” - **Growth Signals**: - Small but highly skilled team (4–5 employees) with backgrounds from Amazon, Intel, Cloudflare, etc. - Awarded non‑dilutive state funding in 2023 - Active product development and hiring (Machine Learning Internship posted) - Growing LinkedIn following (+4.1% yearly) ## Competitive Advantages - **Neurosymbolic AI approach**: Combines deep learning (handling noisy data) with symbolic AI (explainable reasoning, data‑efficient learning) – a differentiator from pure LLM‑based competitors. - **Real production code, not agent chains**: Generates actual deployable code with full version history, testing, and CI/CD – not prompt wrappers. - **Self‑maintaining**: Automatically detects and fixes errors, monitors API changes, and submits updates for approval. - **Enterprise‑grade security**: SOC2 Type II, Google CASA Tier 2, SSO/SAML, RBAC, audit logging, dedicated infrastructure, 99.9% uptime SLA. - **Natural language control**: Users edit requirements in plain English; code updates accordingly – no tickets, no sprints, no waiting. ## Strategic Focus - **Current priorities**: Scaling the neurosymbolic AI platform to handle more complex enterprise use cases; building out integrations; expanding the team (hiring ML interns); maintaining a product‑focused, research‑driven culture. - **Direction for growth**: Democratizing custom software creation so non‑engineers can generate reliable automations, while keeping advanced customization available for developers. ## Why Work Here - **Culture highlights**: Small, tight‑knit team of high‑enthusiasm, low‑ego individuals. “Play hard, work hard” ethos – office located in Louisville, CO (15‑20 min from Boulder), with easy access to hiking, mountain biking, skiing, and trail running. Group dinners, dartboard tournaments, and conversations ranging from causality to baking. - **Remote/hybrid/office policy**: On‑site in Louisville, Colorado (employees work from physical offices). Not remote‑first. - **Notable perks or engineering culture**: - Work on cutting‑edge neurosymbolic AI (not just LLM prompt engineering) - Tech stack: Python, TypeScript, React, PyTorch, FastAPI, Node.js, Kubernetes, Docker, Prometheus, etc. - Emphasis on research and production‑grade science - Internship program available (Machine Learning Internship) - Founders are repeat entrepreneurs with deep technical backgrounds ## Sources 1. [durable.ai/about](https://durable.ai/about) 2. [durable.ai/](https://durable.ai/) 3. [durable.ai/careers](https://durable.ai/careers) 4. [builtin.com/company/durable](https://builtin.com/company/durable) 5. 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