AI Automations Engineer

About Pattern

Pattern (Nasdaq: PTRN) accelerates brands on global ecommerce marketplaces using proprietary technology and AI. Leveraging 46+ trillion data points and advanced machine learning models, Pattern optimizes and automates key levers of ecommerce growth—including advertising, content management, logistics and fulfillment, pricing, forecasting, and customer service. Hundreds of global brands use Pattern’s platform to drive profitable growth across 60+ marketplaces such as Amazon, Walmart, Target, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. Learn more at pattern.com.

Recognition

• Deloitte Technology Fast 500 (North America) honorees.
• Inc. Best-Led Companies.
• Newsweek’s Global Most Loved Workplaces.

Role Overview

As an AI Automations Engineer, you will collaborate with business units to identify high-impact, repetitive processes and deliver AI-powered workflow automations that save time, reduce costs, and improve quality for our day-to-day ecommerce trading and operations—using tools we already have (n8n, MCP, Zapier). You’ll own design, build, operation, adoption, performance uplifts and ROI for these workflows, with engineering collaboration only when hardening, security, or platform-level integration is required. Most automations are short to mid-term (from a few weeks to 6 months) solutions that deliver quick and measurable wins; high impact workflows or projects may be graduated and hardened as a bullet-proof solution over time.

This is a full-time role based in Hong Kong (Hybrid). Reporting into Head of Product Management, APAC.

Day‑to‑Day Responsibilities

• Build and operate AI workflows and agentic patterns using tools like n8n, MCP, and Zapier (flows, prompts, connectors, guardrails).
• Run discovery with business units/departments to target repetitive/manual processes; size impact (time saved, error reduction, cost/run).
• Manage an intake queue and collaborate with the head of the department to prioritize a backlog/short roadmap by impact, effort, and risk; ship in small increments (pilot, measure, iterate, scale).
• Create lean Automation Specs (one-pagers) with triggers, inputs/outputs, data sources, edge cases, fallback/rollback, SLAs, and a simple flow diagram and test checklist.
• Operate production automations: monitor health, triage incidents, manage quotas/limits, and optimize costs (batching, caching, provider/routing strategies).
• Train junior team members—assign and review intake triage, documentation, QA/UAT, data checks, and training assets; set weekly goals; provide feedback and skills development in SQL, metrics, and workflow tools.
• Train and enable business units/departments: documentation, SOPs/runbooks, training videos, workshops/office hours to drive adoption and self‑serve where appropriate.
• Advise teammates building their own flows; share best practices for the foundational AI layer, guardrails, and evaluation.
• Configure and extend internal AI tools (e.g., Open WebUI, workflow plug‑ins) and identify successful experiments to graduate or deprecate.
• Engage Engineering for platform needs (e.g., new/custom connectors, SSO/permissions, sensitive data integration, observability, or hardening at scale) with concise one‑page requests.
• Track and report outcomes: hours saved, cost per run, success/error rates, latency/quality, adoption/utilization, MTTR, and net ROI.

Requirements for Success

• 3 to 5 years’ experience in business process re‑engineering, data analytics, software engineering or enterprise automation roles; hands‑on experience with low/no‑code tools or GenAI is a must.
• Fluency in English and Mandarin (written and spoken) is required.
• Obsession with learning about LLMs and AIs, plus judgment on when not to use them (AI as an accelerant, not a crutch).
• Hands‑on experience with n8n, Zapier, Make, MCP, or similar; comfortable building, testing, instrumenting, and maintaining automations.
• Data skills: SQL required; basic Python preferred (R/Scala familiarity is a plus) to query data, validate outputs, and instrument flows.
• Understanding of core software/ops practices: versioning, change control, monitoring/alerting, and basic CI/CD concepts.
• Sound familiarity with cloud/data concepts (e.g., AWS S3/DynamoDB, REST APIs, webhooks) and how they influence workflow design.
• Working knowledge of LLMs and agentic systems (RAG/vector search, prompt design, evaluation, safety); Western model families and strengths: OpenAI GPT‑5 or 4o, Anthropic Claude, Google Gemini, Perplexity; Microsoft Copilot.
• China counterparts and specializations: Alibaba Qwen/Wan, ByteDance Doubao, Moonshot Kimi, Baidu ERNIE/Wenxin, Zhipu GLM, iFlytek, and Tencent Hunyuan.
• People leadership: experience mentoring or onboarding peers; able to manage and delegate, review work, and give structured feedback to junior team members working on AI Automation.
• Excellent communication and documentation skills to align stakeholders, write clear specs/runbooks, and deliver effective training.

High Performance Indicators

• Deliver automations that measurably improve time, cost, and quality with clear before/after data.
• Backlog and roadmap reflect sharp prioritization and fast iteration; pilots graduate or retire quickly.
• Run disciplined experiments, put practical guardrails in place, and keep production workflows stable with low error rates.
• Junior AI automation team member grows into a capable builder under your guidance, and teams adopt your solutions; usage, satisfaction, and ROI demonstrate sustained value.

Desired Personal Traits

• Game Changers—challenge assumptions, share new ideas, reassess plans with realistic timelines, and pursue improvements that drive results.
• Data Fanatics—use data to understand problems, make unbiased decisions, and track effects over time.
• Partner Obsessed—communicate clearly, listen actively, and deliver outcomes that exceed expectations.
• Team of Doers—uplift teammates, take initiative, support improvements, and hold yourself accountable.

Hiring Process

1. Initial phone interview with Pattern’s talent acquisition team.
2. Hiring manager interview, including a short session to have practical discussion and automation walkthrough (can be your past work or a light take‑home after interview).
3. Behavioral interview with cross‑functional leader and senior leader.
4. Top grading interview.
5. Executive review.
6. Offer.

How to Stand Out

• Bring examples of shipped automations with quantified impact; share flow diagrams (n8n/MCP/Zapier), dashboards, or enablement materials.
• Be ready to discuss discovery, prioritization, guardrails, cost control, and how you drive adoption.
• Show how you would make a difference at Pattern across our marketplaces and product pillars.
• Highlight any side projects related to AI, automation, or analytics.