Your opportunity

Our client is a Toronto technology company building a platform for homeownership: one place for homeowners to understand, maintain and improve their homes, paired with a home services marketplace that connects them with trusted local tradespeople. The company focuses on the Greater Toronto Area by design, building density neighbourhood by neighbourhood before looking further afield.

The business is deliberately different from most of its category. Many home services marketplaces charge commissions that the best tradespeople will not accept, which keeps the market fragmented and gives providers every reason to work around the platform. Our client keeps commissions low so that homeowners, providers and the company all come out ahead. In a market that runs on trust, it takes a patient, long-term approach rather than chasing short-term growth.

Engineering is organized into small, self-contained, cross-functional teams that each combine product, design and engineering and own their work with as few outside dependencies as possible. Most teams build for homeowners and service providers, while others build platform foundations and internal tools. The organization is growing steadily as the product matures.

AI is already part of the marketplace experience, and the company is investing in bringing more intelligence to homeowners and service providers, from maintenance guidance and contractor matching to document understanding and conversational experiences that will continue to evolve. The work applies commercial LLMs, vector search and existing machine learning frameworks to real homeowner problems rather than training original models, so it suits an engineer who enjoys applying AI to product needs more than one motivated by research.

As one of several new AI Engineers, you’ll join a cross-functional team and help shape how the company builds AI features as that capability extends across the engineering organization. The mandate is to build, maintain and keep improving AI features in production rather than launch them and move on, and to work beyond the AI layer across backend, frontend and infrastructure wherever the team needs you. The company is open to candidates at intermediate, senior and staff levels.

The team works together in person every Monday and Thursday and every second Tuesday, and hires people who live within the service area so they can use the product themselves.

Key responsibilities

• AI feature development: Design, build and ship LLM-powered and agentic features for homeowners and service providers

• End-to-end ownership: Own features from API and prompt or agent design through testing, deployment and monitoring in production

• Long-term evolution: Maintain, evaluate and improve AI features after launch as models, data and user behaviour change

• Quality and evaluation: Apply testing, code review and incremental delivery to LLM-based features, including evaluation and regression testing of prompt and agent behaviour

• Model integration: Integrate commercial LLM APIs, vector search and agentic frameworks into the existing Python and TypeScript stack, weighing cost, latency and rate limits

• Full stack contribution: Work beyond the AI layer across backend, frontend and infrastructure as the team’s priorities require

• Product discovery: Partner with product, design and engineering teammates to decide where AI belongs in the product next, rather than executing a fixed spec

• AI engineering practice: Help establish the patterns and conventions the company will use to build and maintain AI features as the capability grows

Tech stack

• AI service: Python

• Vector database: Pinecone

• Product: TypeScript, Node.js, React, React Native

• Databases: PostgreSQL, MySQL, MongoDB

• Infrastructure: AWS, Kubernetes, Terraform

Your know-how

• You have hands-on experience building LLM-powered features for commercial software

• You have maintained and improved AI features in production over time

• You have strong software engineering fundamentals

• You have built and shipped features in a production SaaS web application and can work across the stack, from backend APIs to the LLM and agent layer

• You have experience with agentic frameworks such as LangChain, PydanticAI, LangGraph or an equivalent

• You have deployed and operated production services in a cloud environment

• You understand the cost, latency and rate-limit trade-offs of LLM APIs when designing production features

• You care more about shipping a feature that works for real users than a model that scores well offline

• You are an effective collaborator across functions who can explain technical ideas to people with less context, including junior teammates

• You hold clear opinions and change them readily in the face of better information

It’s a bonus if

• You have worked with a Python async web framework such as FastAPI and a document database such as MongoDB

• You have experience with TypeScript

• You have used Claude Code or similar AI-assisted development tools

• You have built vector search or retrieval pipelines

• You have owned features end to end in a small team or early-stage SaaS company

• You have built products for consumers or small businesses, ideally in home services, construction or a related field

Interested in learning more?

Please send your resume or LinkedIn profile URL to talent@lutrapartners.com with “AI Engineer, Home Services” as the subject line. One of our partners will be in contact shortly.