Artificial Intelligence Engineer

About the RoleWe’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 Do1. 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)2. 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 datasets3. 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 adoption4. 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 accuracy5. Ship Production-Ready Systems- Optimise performance, latency and cost (LLM usage)- Build scalable, reliable services (not prototypes)- Continuously improve models using hiring outcomes and feedbackWhat We’re Looking ForCore 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 applicationsTechnical 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 fast-moving, build-first environmentNice 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 sectorsWhat 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 identificationWhy 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