Junior AI Engineer (Contract)

Looking to take your digital career to a whole new level?

Then this role is for you!

First Page is a certified ?GREAT PLACE TO WORK? and is a global digital marketing firm that transforms the way companies do business online.

Since 2011 our mission has been to create amazing digital experiences by implementing game-changing digital strategies.

As APAC?s highest-rated digital agency, First Page has seen insane growth and won numerous awards over the past 3 years.

About The Role

As an AI Engineer, you will design, build, and ship agentic workflows and AI-powered tools ? primarily for our own internal operations, with a path toward client work as we grow.

You'll turn messy real-world processes into reliable systems by combining LLMs, automation platforms, and AI coding agents.

We build fast using AI coding agents ? n8n for orchestration, plus tools like Cursor, Claude Code, OpenCode, and Pi to design and build tools and flows in whatever language the problem demands. The north star is agentic build speed ? shipping things that work, in any stack, without being boxed into one technology.

This is a junior role for someone who wants to build real agentic systems from day one and learn how modern AI engineering, automation, and product thinking come together.

Responsibilities

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Design and build agentic workflows and automations on n8n, plus Zapier / Make where they fit

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Use AI coding agents (Cursor, Claude Code, OpenCode, Pi, etc.) to design and build tools and flows in any language the task requires

? Integrate LLMs into workflows ? primarily Claude and OpenAI, plus GLM, Kimi, Qwen, MiniMax, DeepSeek and others ? for prompt engineering, function/tool calling, and structured outputs

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Build and maintain RAG pipelines: chunking, embeddings, vector stores, retrieval tuning

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Build production-reliable workflows ? error handling, retries, observability, auditability, and versioning ? with guidance and mentorship as you grow into it

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Handle data responsibly: apply data governance and privacy guardrails when working with sensitive information

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Connect APIs and third-party tools into automated pipelines (CRM, databases, SaaS platforms)

? Evaluate and improve workflow quality ? testing, cost and latency optimisation

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Scope MVPs pragmatically by impact and effort; ship iteratively

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Document architectures, prompts, and configurations clearly so the team can run and extend them

Technical Skills

? AI-assisted development fluency ? able to leverage AI coding agents (Cursor, Claude Code, OpenCode, Pi) to design and build solid solutions in any language (Python, TypeScript, etc.) the problem requires, with enough programming foundation to read, verify, and debug what the AI produces

? Hands-on experience calling LLM APIs ? primarily Claude and OpenAI; familiarity with others (GLM, Kimi, Qwen, MiniMax, DeepSeek) a plus ? and writing production prompts

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Familiarity with at least one automation platform (n8n, Zapier, Make)

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Working knowledge of REST APIs, JSON, and basic data structures

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Understanding of RAG concepts (embeddings, vector databases, chunking)

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Eagerness to learn production discipline ? error handling, observability, and data governance. You don't need to arrive with this; we mentor it.

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Comfortable with Git and version control

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Familiarity with LLM concepts: context windows, tool/function calling, evaluation, hallucination mitigation

Personal Attributes

? Self-motivated and a fast learner ? this is the #1 thing we look for.

The field changes weekly; you learn on your own, stay curious, and don't wait to be taught

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Strong attention to detail ? agent reliability lives or dies on edge cases

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Autonomous: comfortable owning a workflow end-to-end with light guidance

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Good communicator ? able to explain AI capabilities and limits to non-technical teammates

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Product mindset: scopes MVPs, prioritises by impact, ships iteratively

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Proactive: you flag problems, propose solutions, and don't wait to be told

Nice To Have

? Exposure to open-source models and tools ? strong plus (Ollama, vLLM, Hugging Face, self-hosted setups)

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Familiarity with agent frameworks (LangChain, CrewAI, LlamaIndex)

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Knowledge of queue-based architecture for scalable agents

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Basic cloud deployment (Docker, serverless)

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SQL basics for validation and reporting

What We Offer

? Real ownership of internal agentic builds from day one ? no toy projects

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Mentorship on production AI engineering, automation architecture, and building rigor

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Hands-on exposure to the latest LLMs, tools, and agentic patterns

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An AI tooling budget to build fast

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A collaborative, fast-moving startup environment

? Potential for conversion to a full-time role based on performance