About the Role

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

Our platform combines

- Proprietary recruitment data
- A domain-specific knowledge graph (developed with UWA)
- LLM-powered workflows

…to help companies identify, assess and secure critical talent faster.

We’re looking for an AI Engineer to turn this into a working product — building the systems that power candidate matching, ranking and decision support.

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

What You’ll Do

- Build the Talent Intelligence Engine
- Develop candidate-to-role matching and ranking systems
- Combine structured (roles, tenure) and unstructured data (CVs, profiles)
- Apply domain-specific logic (e.g. project scale, commodity exposure, tier 1 vs tier 2 experience)
- Develop LLM-Powered Features
- Build “explainability” layers (why a candidate fits 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
- Integrate AI into Real Workflows
- Embed AI capabilities into ATS platforms like JobAdder and Workable
- Ensure outputs are usable by recruiters and hiring managers
- Focus on speed, usability and real-world adoption
- Build Data Pipelines & Intelligence Layers
- Ingest and structure CVs, job ads and candidate data
- Link entities (companies, roles, projects) into a unified data model
- Work with our knowledge graph to improve matching accuracy
- Ship Production-Ready Systems
- Optimise performance, latency and cost (LLM usage)
- Build scalable, reliable services (not prototypes)




- Continuously improve models using hiring outcomes and feedback

What We’re Looking For

Core Experience

- 3–7+ years in software engineering, ML engineering or applied AI
- Experience building production AI systems (not just notebooks)
- Strong Python skills and experience with modern AI frameworks
- Experience working with LLMs (OpenAI, Bedrock, etc.) in real applications

Technical Capability

- Experience with:
- NLP / 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 (AWS preferred)

Mindset (critical)

- Product-focused — cares about outcomes, not just models
- Pragmatic — can ship quickly and iterate
- Commercially aware — understands what “better hiring outcomes” means
- Comfortable working in a quick-moving, build-first environment

Nice to Have

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

What Success Looks Like (First 3–6 Months)
- Delivered a working candidate ranking and matching model
- Built an AI explanation layer for shortlist decisions
- Embedded AI into a search → shortlist workflow
- Improved speed and quality of candidate identification

Why Join

- Build a category-defining product in a massive industry (energy & resources)
- Work directly with leadership on product and strategy
- Own core IP — the intelligence layer is our moat
- Move fast, ship real features, and see direct commercial impact

📌 AI Engineer – Workforce Intelligence Platform (Perth)
🏢 Kerner Norland
📍 Perth