Overview
Who We Areemater is a fast-growing, performance-driven e-commerce company — the parent company behind four DTC brands creating global impact. Based in Miami, with offices in Armenia and Israel and a team spanning the globe, we handle everything in-house from A to Z: operations, marketing, product development, and customer experience.
At emater, we believe that great results come from unity, responsibility, and contribution.
We build together, take responsibility for what we’ve been given, and create real value — for ourselves and for others.
Our work doesn’t stop with us.
What we build reaches beyond our company — to our customers, our partners, and people around the world.
About the Role
We operate four Shopify stores supported by a portfolio of in-house custom apps and integrations, hosted on our VPS and central to how our brands run. We are looking for a Senior Platform Engineer to take ownership of this stack and evolve it into an AI-first platform that powers end-to-end Shopify store management.
1) Evolve the existing apps — whether they remain as several or consolidate into fewer — into a configuration-driven system where per-store behavior changes by editing config, not by shipping new code.
2) Expose the platform through clean surfaces — API,MCP servers, A2A endpoints, webhooks, structured tools — and architect the internal AI tooling layer that consumes them, so agents and humans can run our stores end-to-end.
You should be highly proficient with Claude Code and modern agentic / “vibe coding” workflows, and bring the rigor those tools alone cannot: sound design, secure code, tested code, repeatable deployments.
1. Platform Architecture & Configuration
2. AI-First Endpoints & Internal AI Tooling
3. Engineering Foundations & CI/CD
– CI/CD: stand up the pipeline from scratch — testing, linting, type checks, security scans, staged deploys, one-click rollback.
– Environments: proper dev, staging, and production with seeded test data and parity.
– Testing: define and enforce a strategy — unit, integration, contract, E2E — with coverage targets that mean something.
– Code quality: standards, PR templates, review SLAs, branching, release process.
– Security: secrets, dependencies, Shopify scopes, customer data.
– Observability: logging, metrics, error tracking, alerting — minutes-not-days awareness.
4. AI-Assisted Development Excellence
– Vibe coding at scale: lead by example with Claude Code and agentic dev tools. Define the patterns the team adopts.
– Codebase hygiene for AI: clean module boundaries, strong types, runnable examples, docs written for humans and agents alike.
– Mentorship by example: coach junior and mid-level engineers through reviews, pairing, and shipping alongside them.
– Reliability: set SLOs, monitor against them, reduce on-call burden over time.
Good to Have
– Shopify experience: custom apps, Admin/Storefront APIs, GraphQL, webhooks, App Bridge, OAuth, Billing API, multi-store ops. Strong specialists are rare; we’ll trade prior Shopify for a strong platform engineer who ramps fast.
– Shopify at scale (Plus, multi-store, headless / Hydrogen).
– Turning hardcoded per-tenant logic into a configuration-driven platform.
– MCP servers, A2A endpoints, or other agent-interop surfaces in production.
– Adjacent stack: Klaviyo, Freshdesk, Finale, ShipStation, BigQuery, GCP.
– Open-source contributions, technical writing, or visible mentorship.
- Own the existing stack: audit, document, and take responsibility for the custom apps across our four stores and VPS.
- Make it configuration-driven: refactor hardcoded, store-specific logic so per-store change is a config change, not a code change. One platform vs. several apps is your call — config-driven is non-negotiable.
- Plan and execute the evolution: decide what consolidates, stays separate, or gets rewritten. Migrate with near-zero downtime and a rollback plan at every step.
- Roadmap: maintain a prioritized engineering roadmap aligned with brand and ops priorities.
- 6+ years of professional engineering experience, 3+ years owning production systems end-to-end.
- System design: configurable multi-tenant systems from first principles; can explain trade-offs to non-engineers.
- Backend & platform engineering: production proficiency in Python and/or Node.js/TypeScript. Comfortable with data modeling, performant SQL, idempotent APIs, multi-tenant config, concurrency.
- CI/CD & DevOps: GitHub Actions / GitLab CI, Docker, IaC. You don't need a DevOps team to ship safely.
- AI-first development: strong, current proficiency with Claude Code and other agentic tools. Shipped non-trivial production code with them.
- LLM, agent & interop: OpenAI/Anthropic APIs, MCP, A2A or comparable protocols, tool use, structured outputs, evaluation.
- IC leadership: raise the bar through reviews, design docs, and mentorship — without becoming a bottleneck, as well as design and implement new SOPs
- Operational mindset: cost, security, observability, and on-call before you ship.
- Communication: can write a design doc, run a code review, push back on scope, explain decisions to non-technical stakeholders.
- AI-native API design: endpoints meant to be consumed by agents — well-documented, idempotent, deterministic where it matters, observable.
- Agentic store operations: build the primitives for end-to-end store management (catalog, inventory, orders, support, merchandising, content) with the right guardrails and audit trails.
- MCP, A2A & interop: expose capabilities via MCP servers, A2A endpoints, webhooks, and structured tools. Track these standards as they evolve.
- Architect the internal AI tooling layer: design and build the agents that consume the platform, plus the shared scaffolding (prompts, evals, memory, routing). First-class part of the role.
- Evaluation & drift control: build eval harnesses so we catch regressions, hallucinations, and drift before users do.
- Paid days off, medical insurance, 13th salary, wellness benefits, and referral bonuses.
- A collaborative, supportive environment where your ideas and professional growth are highly valued.
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