Job Description
This is a remote position.
₱170,000–200,000/month | Contractor | 100% Work From Home | Australian Business Hours | Health & Nutrition Tech Startup
If you’ve shipped production LangGraph systems and want to own the AI architecture at a fast-growing health tech startup — this role was built for you.
We’re placing an AI Engineer for a fast-growing Australian nutrition and technology company building the next generation of their AI-powered personalisation engine. You’ll architect and implement LangGraph-based agent systems, design multi-step reasoning workflows, build RAG pipelines, and integrate LLM providers into production-grade conversational systems. You’ll work closely with the Head of Engineering and Product team and own real architecture decisions that directly impact user experience for thousands of people.
This goes beyond prompt engineering. If you build graph-based agent workflows, know how to manage conversational state at scale, and want to work on something that creates real health outcomes for real users — apply now.
WHAT YOU’LL BE BUILDING
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A LangGraph-powered conversational nutrition assistant with stateful memory and structured outputs
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Multi-step reasoning workflows combining user profile data, behavioural data, and contextual signals
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Tool-enabled agents that query internal APIs and databases for personalised recommendations
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RAG pipelines for domain-specific nutrition knowledge using embeddings and vector databases
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Middleware in Node.js and Express to support AI orchestration
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Observability, logging, and evaluation frameworks for LLM outputs
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Systems that improve reliability, latency, and cost efficiency of production AI
Requirements
Must Have
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3+ years experience as an AI or ML engineer building and deploying production systems
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Hands-on LangChain experience and strong production LangGraph experience
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Deep understanding of agent design patterns — tool use, memory handling, graph orchestration
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Experience integrating OpenAI, Anthropic, or similar LLM providers into structured agent pipelines
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Strong backend experience with Node.js and Express
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Experience implementing RAG pipelines with embeddings and vector databases
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Practical knowledge of prompt design, structured outputs, and evaluation frameworks
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Experience with user behavioural data and recommendation systems
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Python familiarity for AI experimentation, evaluation, or model workflows
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Experience deploying AI systems on cloud platforms — AWS, GCP, or Azure
Preferred
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Experience building AI systems in health, nutrition, or wellness
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Experience with sensitive user data, AI safety, guardrails, and responsible AI practices
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Experience in fast-moving startup environments
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Experience building multi-agent or hybrid deterministic plus LLM systems
Benefits
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₱170,000 – 200,000 per month
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Contractor arrangement — direct payment
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100% work from home
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Monday to Friday | 8:00 AM – 5:00 PM AEST
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Long-term role with a fast-growing Australian health tech startup
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Own real architecture decisions that ship to production
If you build production agentic AI systems and want to own the architecture at a startup that’s creating real health outcomes — apply now.