Aigents.au Engineering Fellow Brief • Verified Candidate

Kate Corcoran (ATAR 99.00) × Apex Clean Energy & Minerals

Systems & Automation Engineer (Vacation / Undergraduate / Junior) | Decarbonisation & Fleet Automation
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The Complementary Model: Senior engineers spend up to 50% of their week wrangling telemetry data, cross-referencing compliance clauses, and writing repetitive scripts. Kate Corcoran combines top 1% academic rigor with enterprise AI workflow harnesses to absorb this operational drag on Day 1, allowing your lead engineers to focus purely on high-leverage delivery.
⚡ Role Complementarity Matrix
Advertised Role Need Existing Senior Team Drag How Kate Corcoran + AI Solves It
Telemetry & Sensor Data Analysis Senior engineers lose 15+ hours/week manually parsing noisy CSV sensor logs and diagnosing transient battery fault codes.
Automated Anomaly & Telemetry Parsing
Python + Polars data pipelines augmented with agentic anomaly detection to wrangle dirty sensor logs and time-series data without manual data cleaning drag.
PythonPolarsPandasDuckDBAgentic Pipelines
Standards & Regulatory Auditing Manual cross-referencing of AS/NZS electrical and mechanical compliance specs creates bottlenecks before equipment sign-off.
Automated Anomaly & Telemetry Parsing
Python + Polars data pipelines augmented with agentic anomaly detection to wrangle dirty sensor logs and time-series data without manual data cleaning drag.
PythonPolarsPandasDuckDBAgentic Pipelines
Technical Documentation & Risk Registers Engineers are backlogged updating FMEA matrices, HAZOP logs, and weekly shift handoff documentation.
Automated Anomaly & Telemetry Parsing
Python + Polars data pipelines augmented with agentic anomaly detection to wrangle dirty sensor logs and time-series data without manual data cleaning drag.
PythonPolarsPandasDuckDBAgentic Pipelines
Simulation Scripting & Parameter Testing Writing repetitive parameter sweep scripts for battery thermal models drains lead engineering time.
Automated Anomaly & Telemetry Parsing
Python + Polars data pipelines augmented with agentic anomaly detection to wrangle dirty sensor logs and time-series data without manual data cleaning drag.
PythonPolarsPandasDuckDBAgentic Pipelines
🎓 Verified Academic & Technical Proof Points
ATAR 99.00
ATAR Academic Rank (Top 1%)
First Class Track
Bachelor of Engineering (Honours)
3 Days
Onboarding to Production Output
Key Technical Projects
Automated Heavy Asset Telemetry Parser: Engineered an agentic ingestion pipeline parsing 500k+ sensor data points per second, detecting thermal and vibration anomalies in heavy rotating machinery. (Reduced manual telemetry diagnostic time by 80%.)
Australian Standards Compliance Assistant: Built a sovereign, local RAG retrieval system indexing heavy vehicle, mechanical safety, and pressure vessel standards to cite applicable clauses in seconds. (Turned a 4-hour manual standards review into a 2-minute verified report.)
Placement Terms & Availability
Engagement: 8–12 week high-impact vacation sprint or flexible co-op.
Location: Brisbane / Hybrid / Site Travel.
Interactive Portal: Test the live technical Q&A AIgent at apex-energy.aigents.au.
Scheduling: 15-minute technical fit interview available on request.