Artificial Intelligence Engineer

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 1. 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 datasets 3. 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 4. 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 5. 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 fast-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