The role
OODARIS is the Agentic OS for Retail Decisions. Every night it finds what moved in a retailer's business, explains why and proposes a fix that a planner approves in the morning. ALDO Group backs OODARIS and runs it in production across ALDO, Sperry, Call It Spring and G.H. Bass.
We are early. OODARIS covers five merchandising decisions: merchandise financial planning and open-to-buy are in production at ALDO Group, and all five are available to new clients. You will work directly with the founder and our engineers, and with the planners who use what you build.
You will own the product surfaces: the screens where a planner sees what moved, reads why, asks OODIE (the agent people talk to) a question, and approves or rejects a proposed fix. By default, nothing is written back until the decision's owner approves, so the approval flow has to be clear and leave a full audit trail.
The front end is React 19 and TypeScript in strict mode, with Tailwind, shadcn/ui, React Hook Form with Zod, Zustand and TanStack Query, tested with Vitest and Playwright. It talks to a typed FastAPI backend-for-frontend (BFF), with contracts in OpenAPI and JSON Schema; the backend services run in Docker containers.
What you will do
- Build the approval flow, with role-based access and an audit entry for every decision a planner makes.
- Build the agent run view: streamed output and tool events over SSE, so a planner can follow what an agent did.
- Build data-dense views, such as virtualized grids, timelines and trace viewers, that stay fast on large plans.
- Keep the UI, the BFF and the services on one set of typed contracts, with clients generated from OpenAPI.
- Build connector setup flows with retries and strict schema validation.
- Set performance budgets for key screens and enforce them in CI.
- Cover the critical paths with Vitest and Playwright tests.
- Make every screen work with a keyboard and a screen reader.
Your first 90 days
- Day 30: a first change to a production screen shipped, with tests and its baseline Web Vitals recorded.
- Day 60: one product surface that you own end to end, such as the approval flow or the agent run view, with a performance budget enforced in CI.
- Day 90: an improvement to that surface shipped and measured against its day-60 baseline, with Playwright tests on its critical paths.
What you bring
- 5+ years building web products, with production work on both the front end and the API.
- A data-dense React and TypeScript application you shipped that people used for their daily work.
- A typed API you designed and then changed over time without breaking its clients.
- A Python backend service you built and ran in production, with FastAPI or a similar framework.
- A slow screen you made fast, with the numbers from before and after.
- Clear writing: design notes and pull requests that other engineers can review quickly.
It helps if you have built a design system, worked in depth with WCAG and ARIA, or built interfaces for LLM products, such as streamed output, tool calls or evaluation dashboards.
Location
Montréal is preferred; remote in Canada also works, with core hours on Eastern Time. French is an asset, not a requirement.
Hiring process
- A 30-minute intro call.
- A technical conversation: walk us through a product you built, from the API to the screen, and the trade-offs you made in its UI architecture, API layer or performance.
- A practical session: work through a realistic problem from our product with our engineers.
- Conversations with the team, including product and engineering.
- A final conversation with the founder, and reference calls with former managers.
How to apply
Use the form on this page, or email careers@oodaris.ai with "Full Stack Engineer" in the subject line. Tell us about a product you built: who used it, how you knew it was fast enough, and one decision you would make differently today.
Hiring manager

Fatih Nayebi
Founder & CEO
Key facts
- Team
- Product Engineering
- Focus areas
- Planner-facing interfaces, Typed APIs, Performance and accessibility
- Questions?
- careers@oodaris.ai
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