Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 22, 2026.
- A LangGraph powered conversational nutrition assistant with stateful memory, structured outputs and guardrails
- Multi step reasoning workflows that combine user profile data, behavioural data and contextual signals
- Tool enabled agents that query internal APIs and databases to generate personalised recommendations
- Retrieval augmented generation pipelines for domain specific nutrition knowledge, using embeddings and vector databases
- Middleware in Node.js and Express to support AI orchestration
- Observability, logging and evaluation frameworks for LLM outputs
- Systems that get measurably more reliable, faster and cheaper to run over time Why this role is worth having Most AI engineering jobs are one feature inside someone else’s architecture. This is the architecture. You are the person who decides how the graph is structured, how state is managed, how retrieval is tuned and how the whole thing is evaluated. It also does not stop at the assistant. equ has a roadmap of AI work behind this, including advanced recommendation engines and intelligent coaching features, and the person who builds the first system is the person who shapes what follows. You will be working in agent orchestration, the fastest moving area in applied AI right now, on a product where the output is a measurable health outcome for a real person.
Requirements
- At least 3 years of experience as an AI or ML Engineer building and deploying production systems
- Strong production experience with LangGraph, and hands on experience with LangChain
- Experience with LangSmith for tracing, evaluation or monitoring of LLM systems
- Deep understanding of agent design patterns, including tool use, memory handling and graph orchestration
- Strong backend experience building services in Node.js and Express
- Experience implementing RAG pipelines in production with embeddings and vector databases
- Practical knowledge of prompt design, structured outputs and evaluation frameworks
- Experience integrating OpenAI, Anthropic or similar LLM providers into structured agent pipelines
- Availability to work Monday to Friday, 7:00 AM to 4:00 PM Philippine time Nice to have
- Python for AI experimentation, evaluation or model workflows
- Experience deploying AI systems on AWS, GCP or Azure
- Experience with user behavioural data and recommendation systems
- Experience building AI for health, nutrition or wellness products
- Experience designing systems that handle sensitive personal data
- Familiarity with AI safety, guardrails and responsible AI practice
- Experience building multi agent or hybrid deterministic plus LLM systems
- Experience in fast moving startup environments
Benefits You will be engaged by Offshore 24/7. We have been placing Filipino professionals with businesses overseas since 2008, more than 500 of them, and our people rate us 4.9 out of 5 on Glassdoor and 5.0 on Google. That rating is about how we look after the people we place, which is the part most candidates cannot check before they sign. We also run our own training and professional development programme, so your growth is not dependent on how much time a client has to spare.
Benefits
- ₱180,000 to ₱200,000 per month
- Contractor arrangement with direct payment
- 100% work from home
- Monday to Friday, 7:00 AM to 4:00 PM PHT
- Long term, ongoing role with a fast growing Australian health technology company
- Ownership of real architecture decisions that ship to production
- Annual rate and performance review
- Comprehensive training and ongoing professional development
- Regular staff events and team activities
• Direct exposure to Australian clients and business practices Before you apply, three things are genuinely essential: LangGraph in production, not prototypes. Node.js and Express backend work you have owned. RAG pipelines you have shipped and tuned yourself. If that is you, we want to talk.

