Are you ready to help build innovative products from the ground up with a team transforming the accounting industry? Invictus is growing, and weâre looking for talented software engineers to join us as we develop leading-edge technology solutions for finance and accounting.
At Invictus, youâll work alongside passionate professionals developing groundbreaking tools - some for commercialization, others to streamline and automate our internal processes. Youâll gain hands-on experience with the latest in AI, NER, cloud, and automation technologies as you help shape the future of financial reporting.
We are seeking a
Software Engineer
to help power the core intelligence of our financial statement automation platform. This is not a role where you simply call external APIs. Here, you will fine-tune Transformer models and applying heuristic rules as well as deterministic logic to interpret the nuance, structure, and semantics of financial reporting.
The Role: Software Engineer - Full Stack Developer
This is a hybrid full-stack role focused on building the core intelligence behind our financial automation platform. Youâll write application logic, train Transformer models, build APIs that serve ML inference, and collaborate with CPAs and domain experts who understand IFRS and US GAAP inside out.
Itâs a hands-on engineering position where youâll work across the stack, refine NER and classification models, and contribute features that get used by real accounting teams. You wonât just call external APIs. Youâll train, deploy, and optimize your own.
Ideal for a junior or intermediate engineer with roughly two to five years of professional experience who wants serious responsibility, technical growth, and an environment that values curiosity.
What Youâll Do
Full-Stack Engineering and ML Integration
Build and maintain backend features in Python and contribute to frontend functionality where needed.
Develop and extend FastAPI endpoints that serve model inference in production.
Troubleshoot issues across the stack, from data preprocessing to API performance.
Assist in integrating .NET Core components that connect ML workflows to application logic.
Model Training and Document Intelligence
Fine-tune BERT based models for NER, token classification, and text extraction.
Train models using LoRA, QLoRA, and other PEFT methods for performance and cost improvements.
Implement tokenization, preprocessing, and dataset curation pipelines tailored to financial documents.
Collaborate with CPAs to build high quality datasets grounded in IFRS and US GAAP structure.
Quality, Research, and Reliability
Write clean, well tested code across training, inference, and deployment workflows.
Participate in code reviews with backend and ML teams to uphold engineering standards.
Track precision, recall, and error patterns to guide iteration.
Stay up to date with applied NLP research and bring new methods into production when they move the needle.
Cross Functional Collaboration
Work directly with backend engineers, ML engineers, and product managers.
Coordinate with offshore partners to bring R\&D prototypes into production.
Communicate model behavior and limitations clearly to both technical and non technical stakeholders.
What You Bring
Technical Foundations
Strong Python development skills, ideally with FastAPI.
Understanding of async patterns, Pydantic models, and containerization.
Hands-on experience fine-tuning Transformer models using Hugging Face tools.
Familiarity with LoRA, QLoRA, quantization, and GPU optimization best practices.
Experience deploying models using Docker and cloud services such as Azure.
Knowledge of NER, sequence classification, or document segmentation.
Mindset and Work Style
Curiosity and a willingness to dive into research when needed.
Comfort moving between backend development and ML workflows.
Strong communication skills and ability to collaborate with domain experts.
Attention to detail and pride in writing clean, maintainable code.
Interest in understanding financial document structure even if you arenât from a finance background.
Experience Level
Two to six years of software engineering or ML engineering experience.
Experience shipping production ML models is a strong plus.
Exposure to financial data is a bonus, not a requirement.
Why Youâll Love This Role
Build real ML systems that interpret complex financial documents.
Work directly with CPAs and domain experts, gaining context rarely found in engineering roles.
Join a team that values balance and deep work through the Great Eight methodology.
Contribute to a fast growing technical function inside a well established advisory firm.
Work in a hybrid environment at our Coal Harbour office with flexibility and trust.
Compensation and Work Environment
Hiring for both Junior and Intermediate levels, with compensation aligned to experience and skill level
Salary range: 70k to 100k (flexible for the right candidate)
Hybrid work environment from the Coal Harbour office with flexibility for remote days
Full benefits package, including support for professional development
Ready to Build the Future of Financial Automation?
Apply now. No cover letter required.
About Us
We are not your typical CPA firm.
Located in downtown Vancouver, our 70+ team members provide consulting, accounting, and tax advisory for public and private companies. Our team members enjoy client variety, camaraderie, and a professional yet flexible work environment. Our proprietary âGreat Eightâ methodology ensures a highly effective and balanced eight-hour workday - so you can focus, excel, and still have time for life outside work.