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AI Engineer – Workforce Intelligence Platform

FBC Asia Pacific -
Remote

Quick Apply

Job Details

Full-time
1 hour ago

Qualifications

CRM software
Data modelling
Law
Moving
ATS
Master's degree
Databases
AWS
Natural language processing
Recruiting
Data pipeline
APIs
AI

Full Job Description

AI Engineer – Workforce Intelligence Platform

Job Type: Full-time
Location: Perth, WA / Remote within Australia

About the Role

We’re building an AI-powered workforce intelligence platform for the energy, resources, and infrastructure sectors.

The platform combines proprietary recruitment data, a domain-specific knowledge graph, and LLM-powered workflows to help companies identify, assess, and secure critical talent faster.

We’re looking for an AI Engineer to help turn this technology into a production-ready product by building the systems that power candidate matching, ranking, and decision support.

This is a hands-on product engineering role, not a research position.

What You’ll Do:

1. Build the Talent Intelligence Engine

Develop candidate-to-role matching and ranking systems
Combine structured data such as roles and tenure with unstructured data including CVs and candidate profiles
Apply domain-specific logic such as project scale, commodity exposure, and Tier 1 vs. Tier 2 experience

2. Develop LLM-Powered Features

Build explainability layers to show why a candidate is a strong fit for a role
Generate candidate summaries, comparisons, and shortlists
Create AI-assisted workflows for search, screening, and outreach
Implement Retrieval-Augmented Generation (RAG) over internal datasets

3. Integrate AI into Real-World Workflows

Embed AI capabilities into ATS platforms such as JobAdder and Workable
Ensure AI outputs are practical and usable by recruiters and hiring managers
Focus on speed, usability, and real-world adoption

4. Build Data Pipelines & Intelligence Layers

Ingest and structure CVs, job advertisements, and candidate data
Link entities such as companies, roles, and projects into a unified data model
Work with knowledge graphs to improve matching accuracy

5. Ship Production-Ready Systems

Optimise performance, latency, and LLM usage costs
Build scalable and reliable services rather than prototypes
Continuously improve models using hiring outcomes and user feedback

What We’re Looking For:

Core Experience

3–7+ years of experience in software engineering, ML engineering, or applied AI
Experience building and deploying production AI systems
Strong Python skills and experience with modern AI frameworks
Hands-on experience working with LLMs such as OpenAI, Amazon Bedrock, or similar platforms

Technical Capability

Experience with:
NLP and information extraction from unstructured data
Search and ranking systems
RAG pipelines and vector databases
Solid understanding of:
Data pipelines and ETL
APIs and backend systems
Cloud infrastructure, preferably AWS

Mindset

Product-focused – cares about outcomes, not just models
Pragmatic – able to ship quickly and iterate
Commercially aware – understands what better hiring outcomes mean
Adaptable – comfortable working in a fast-moving, build-first environment

Nice to Have:

Experience in recruitment, HR technology, or marketplace platforms
Exposure to knowledge graphs or entity resolution
Experience integrating with ATS or CRM systems
Familiarity with the energy, mining, or infrastructure sectors

What Success Looks Like in Your First 3–6 Months:

Deliver a working candidate ranking and matching model
Build an AI explanation layer for shortlist decisions
Embed AI into a search → shortlist workflow
Improve the speed and quality of candidate identification

Why Join?

Build a category-defining AI product for the energy and resources industry
Work directly with leadership on product development and strategy
Own and shape core AI technology
Move quickly, ship real features, and see direct commercial impact

Application Question(s):

How many years of experience do you have in software engineering, ML engineering, or applied AI?
Do you have hands-on experience building and deploying production AI systems?
Do you have experience working with LLMs, RAG pipelines, and vector databases?
What is your expected annual salary (AUD)?
What is your availability to start?

Work Location: Remote

Quick Apply

Refine Your Search

infrastructure engineer jobs in fully remote

AI Engineer – Workforce Intelligence Platform

Data Center Infrastructure Specialist

Implementation Engineer, Customer Support (APAC)

Crypto Operations Associate - APAC

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Software Engineer, Flex

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Software Engineer, Billing

Electrical Engineer

Senior Technical Account Manager, ANZ

Senior Product Manager

Manager, Solutions Engineering

SOC Analyst

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