Applied AI Engineer - Enlightened Today (Thunder Bay)

Applied AI Engineer

Enlightened Today is a rapidly expanding and innovative 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. Our business model centers on creating authentic connections with our audience through digital channels and delivering premium services and products that meet their needs.

The Role

This is a hands‑on, embedded engineering role. Instead of sitting behind a backlog and building to spec, you’ll 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’ll 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. This is a “hire for talent” role; we care far more about what you can build and how you think than about your years of experience or pedigree.

What You’ll Build

• Agentic orchestration – We run our development and operations on an internal system of specialized AI agents, built on Claude Code, that plan, build, and review each other’s work before anything ships. You will operate it, extend it, build new agents and skills for our specific workflows, and keep those quality gates sharp.
• Conversational AI grounded in the customer – Build AI chat and voice experiences that tap into a customer’s profile and behavioral signals to have genuinely helpful, personalized conversations with them about their relationship and life questions, the core of what our customers come to us for. This spans retrieval over customer profiles, conversation memory, and real‑time voice on the roadmap.
• Signal‑based personalized marketing – Turn customer signals into tailored marketing: segments, scoring, and personalized messaging pushed through our marketing stack. This extends our existing lead‑intelligence pipeline.

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 of our agent tooling touches shell + TypeScript/Node)

What We’re Looking For

• Hands‑on, embedded instincts: diagnose non‑technical stakeholder needs and turn them into something working fast and without a detailed spec.
• Strong communication: work directly with the founders and explain 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 operated multi‑agent systems; understand orchestration, tool/function calling, and review/eval loops.
• Fluency with AI‑assisted development: use tools like Claude Code daily and know how to get great output from them.
• Solid engineering discipline: testing (we value 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; you can’t be allergic to it.
• A bias toward shipping: working software over perfect software.
• Sound judgment around sensitive, emotional conversations: guardrails, scope limits, escalation paths, and clear boundaries built in.
• Care with personal data: customer profiles and conversation content are sensitive (consent, data minimization, secure storage, 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.
Close to the problem – you will 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.