Full Stack Engineer (AI)

About the Company

Our client is a fast-growing technology company building AI-powered tools that help small businesses operate more efficiently. Their platform leverages modern AI systems to automate complex workflows, enabling business owners to launch and run businesses with significantly less operational overhead.

Since launching in 2022, their AI-powered platform has been used to generate millions of websites and support small businesses across multiple industries. The company is well-funded by top-tier venture investors and is scaling rapidly as they continue to expand their AI product ecosystem.

They are building a new category of AI-driven tools designed to complete real business work autonomously, combining product engineering, applied AI, and modern cloud infrastructure.

About the Role

We’re looking for a Full Stack Engineer (AI) to help build and scale AI-powered product features used by millions of small business owners.

This role sits at the intersection of product engineering and applied AI systems. You will design and build customer-facing features while helping integrate and scale the AI infrastructure that powers them.

You’ll work with a modern AI-native stack including React, NextJS, TypeScript, NodeJS, Python, Postgres, and modern LLM infrastructure, building intelligent workflows, AI agents, and production-ready AI applications.

This role is ideal for engineers who enjoy building end-to-end product features while experimenting with emerging AI technologies and LLM-powered workflows.

What You’ll Do

• Build and ship full-stack AI-powered product features using React, NextJS, and TypeScript.
• Design and implement AI workflows and intelligent agents using techniques such as Retrieval Augmented Generation (RAG), tool calling, memory systems, and reasoning-based workflows.
• Develop scalable backend services and APIs supporting AI-powered applications.
• Collaborate with product, design, and AI teams to integrate new model capabilities and shape product direction.
• Prototype and experiment with emerging AI capabilities, turning research into production-ready features.
• Contribute to the development and scaling of AI infrastructure supporting production systems.
• Stay current with advances in applied AI, LLM systems, and agentic architectures and apply them to real-world product challenges.

What You Bring

• 2+ years of professional software engineering experience building production applications.
• Strong experience with React, NextJS, and TypeScript.
• Solid backend engineering experience building scalable services and APIs.
• Familiarity with applied AI concepts such as Retrieval Augmented Generation (RAG), Chain-of-Thought reasoning, memory systems, or LLM-based workflows.
• Strong understanding of software engineering best practices including testing, code quality, and version control.
• Experience working with relational databases such as Postgres.
• Curiosity and enthusiasm for building with modern AI tools, models, and frameworks.

Nice to Have

• Experience building LLM-powered products, agentic workflows, or multi-modal AI systems.
• Experience deploying AI applications using PyTorch, Hugging Face, or model-serving infrastructure.
• Experience working with vector databases, embeddings, or large-scale AI pipelines.
• Experience shipping AI features or workflows into production environments.

Why This Role

• Opportunity to build AI-first product experiences used by millions of users.
• Work at the intersection of product engineering and applied AI innovation.
• Collaborate with a highly technical team building modern AI infrastructure and tooling.
• Competitive compensation including $180,000 – $225,000 CAD base salary plus equity.
• Hybrid work environment with the option for remote work within Canada.
• Opportunity to contribute to a rapidly growing company shaping the future of AI-powered business tools.

Technologies

• Languages: TypeScript, SQL, Bash, HTML5, CSS3, Python
• Frameworks/Libraries: React, NextJS, React Query, React Native, Expo, TailwindCSS, RadixUI, DrizzleORM, trpc, NodeJS, Bun, WebRTC, PyTorch
• Databases: Postgres (including PGVector and JSON data types), object storage systems
• AI Infrastructure: Together.ai, LangSmith, Hugging Face, Replicate, Langfuse
• AI Engineering: Large Language Models, Multi-modal models, image generation, in-painting