Applied Ai Engineer (Sherbrooke)

Applied AI Engineer

Who We Are

Enlightened Today is a rapidly expanding and creative company leading the charge in the spiritual and wellness space. We are dedicated to changing the industry with bold, creative marketing strategies and forward‑thinking technical solutions. Our team thrives on collaboration, innovation, and crafting content that deeply resonates with our audience.

Role Overview

This is a hands‑on, embedded engineering role. Instead of sitting behind a backlog and building to spec, you embed directly with the founders and the team, figure out what the business actually needs (which is often not what was first asked for), and ship working AI solutions fast. You move fluidly between building AI agents, shipping customer‑facing AI products, and wiring up the data that feeds both, talking to the people who’ll use what you build, iterating in front of them, and turning rough ideas into things that work.

In short: part engineer, part solutions architect, part builder‑who‑talks‑to‑humans. You’ll be deployed against our own business and customers rather than external clients, but the instincts are the same: high autonomy, fast prototyping, strong communication, and a bias toward shipping something useful over perfecting something slowly.

What You’ll Build

• Agentic orchestration – operating, extending, and building new agents and skills for our internal system of specialized AI agents built on Claude Code, keeping quality gates sharp.
• Conversational AI grounded in the customer – building AI chat and voice experiences that tap into a customer’s profile and behavioral signals for genuinely helpful, personalized conversations about relationships and life questions.
• Signal‑based personalized marketing – turning customer signals into tailored marketing segments, scoring, and messaging pushed through our marketing stack.

Our Stack

• AI / LLM: Claude (API + Claude Code), multi‑agent orchestration, prompt and skill authoring, ElevenLabs for voice.
• Primary language: Python.
• Backend / data: Postgres / Supabase (incl. pgvector), REST APIs.
• Frontend: Next.js, React, Vercel, HTML/CSS.
• Marketing infra: Klaviyo, Checkout Champ, Hyros, attribution and CRM tools.
• Tooling: Git/GitHub, CI, modern AI‑assisted dev workflows (some agent tooling touches shell + TypeScript/Node).

What We’re Looking For

• Hands‑on, embedded instincts – diagnosing non‑technical stakeholder needs and turning them into working solutions fast, without a detailed spec.
• Strong communication – working directly with the founders and explaining your work to non‑engineers clearly.
• Strong Python and solid full‑stack fundamentals, comfortable across backend logic, data, and a functional frontend.
• Real, hands‑on LLM experience – prompting, retrieval (RAG), chaining, evaluating outputs, and handling the messy reality of non‑deterministic systems.
• Agentic experience – built or seriously operated multi‑agent systems and understood orchestration, tool/function calling, and review/eval loops.
• Fluency with AI‑assisted development – using tools like Claude Code daily and knowing how to get great output from them.
• Solid engineering discipline – testing (TDD), clean Git workflows, and the judgment to build quality gates rather than skip them.
• Comfortable in shell and TypeScript/Node when the tooling calls for it; not an expert, but not allergic to it.
• A bias toward shipping – working software over perfect software.
• Sound judgment around sensitive, emotional conversations – designing guardrails, scope limits, escalation paths, and clear boundaries for AI that talks about love and relationships.
• Care with personal data – respecting consent, data minimization, secure storage, and compliance with CCPA.

Nice to Have

• Prior solutions‑engineering, founder, or consulting experience, or anything that put you face‑to‑face with the people you build for.
• Experience with conversational/voice AI: TTS/STT, low‑latency streaming, voice‑agent frameworks (LiveKit, Pipecat, Vapi).
• Experience in DTC e‑commerce, subscriptions, or performance marketing.
• Familiarity with attribution/CRM platforms and marketing APIs.
• Recommendation, personalization, or feature‑store experience.
• Familiarity with agentic frameworks (LangGraph, CrewAI, AutoGen, or similar) and the Agent Skills pattern.
• A portfolio of shipped products, repos, demos, or AI projects we can look at.

Why This Role Is Different

• Genuine ownership – direct access to the founders, no layers of approval, and the ability to ship to real customers fast.
• You’re close to the problem – you won’t be handed tickets in isolation; you’ll sit with the business, see the real need, and build for it directly.
• AI‑native by default – you’ll orchestrate AI agents rather than type every line, the way the best engineers will work in a few years.
• Breadth – if you’re tired of being a cog on one narrow feature, this is the opposite. You’ll touch the whole business.