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: In person
