Software Engineer in Canberra

We are seeking a research-oriented Software Engineer with advanced Python and C++ capabilities to develop algorithms, backend services and data-processing components across AI-assisted document-processing and enterprise financial-planning applications. The role combines applied research in document analysis and sensitive-information detection with the implementation of financial calculations and enterprise data pipelines. The common focus is translating complex mathematical and business requirements into accurate, efficient and maintainable software. You will take ownership of technical problems from investigation and prototyping through experimental validation, optimisation and production deployment.

Key responsibilities

• Conduct original applied research: Investigate limitations in existing document-analysis and sensitive-information detection methods, develop and validate improved algorithms, and integrate successful approaches into production software.
• Develop AI-assisted document-processing systems: Build detection and localisation algorithms and human-in-the-loop redaction workflows supporting user review, correction, approval and traceable processing decisions.
• Implement financial calculations and data pipelines: Develop budgeting, forecasting, scenario-modelling, cost-allocation and reconciliation functionality, translating requirements agreed with finance stakeholders into reliable software.
• Deliver production software: Design, implement, test and optimise algorithmic components, backend services and APIs. Document technical approaches and calculation assumptions, and investigate performance, accuracy and data-quality issues.

Essential skills and research background

• Original research and innovation: Demonstrated experience conducting original applied research and developing algorithms relevant to computer vision, machine learning, document processing or related computational methods. Applicants must substantiate their research experience with verifiable references and clearly describe their individual research and technical contributions.
• Python and modern C++: Advanced commercial software-development experience in both languages, including implementing, testing, debugging and optimising computationally intensive algorithms. Experience using Python for research, AI or data-processing development and C++ for performance-critical components, with the ability to translate prototypes into maintainable production software.
• Mathematical algorithm development: Demonstrated ability to apply linear algebra, geometry, numerical methods, optimisation, probability and statistics to practical engineering problems. Experience independently evaluating existing methods, developing original approaches and validating results through reproducible experiments.
• Computer vision and image/video analysis: Experience developing algorithms that locate and track documents or regions of interest in images and video. Ability to identify and match visual features, use projective geometry to align different views and correct perspective, and combine information across frames. Experience maintaining accuracy and computational efficiency under motion, distortion, partial visibility and variable image quality.
• AI-assisted sensitive-information detection and redaction: Experience combining machine learning, spatial analysis and deterministic rules to detect, classify and locate sensitive information. Experience implementing human-in-the-loop workflows, including confidence-based review, correction of missed or incorrect detections, approval controls, reliable removal of content selected for redaction and audit trails. Experience testing and improving the accuracy and reliability of detection algorithms.
• Financial software and calculation systems: Commercial experience implementing financial calculations and processing financial data in enterprise applications, including budgeting, forecasting or driver-based cost allocation. Working knowledge of general-ledger and planning data, including actuals, budgets, forecasts, accounts, cost centres, projects and reporting periods. Ability to translate requirements agreed with finance stakeholders into testable, auditable calculation rules, investigate discrepancies and reconcile outputs to source records.
• Enterprise software and data engineering: Strong SQL, database modelling, backend/API development and data-pipeline experience. Proficiency in automated testing, version control, deployment, access controls and technical documentation. Ability to integrate data from multiple enterprise systems and maintain traceability across source records, transformations and calculated outputs.