Senior Software Engineer: Data @ Fiscal.ai
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Overview
Fiscal.ai (formerly FinChat) is on a journey to build the best financial data company in the era of AI. The company has grown exponentially with a talented founding engineering team and is seeking a true outlier to join as a Senior Software Engineer: Data.
Why Join Fiscal.ai?
Be part of a venture-backed growth story with over 300,000 users and notable enterprise partners. This role offers an opportunity to join the ownership team with equity options, work in a dynamic startup environment, and contribute directly to strategic decision making.
Role Description
You will work on proprietary data technology, focusing on both aggregation and distribution via API. Hands-on experience with financial data, AI technology, and building robust APIs is required.
- Minimum 5+ years experience in Data Development.
- Expertise in data parsing, databases, and Python.
- Solid track record building APIs and handling structured/unstructured data.
- Passion for investing and finance with a technical edge in AI.
- Bachelor’s in Computer Science or equivalent (self-taught considered).
Tech Stack & Bonus Skills
The tech ecosystem includes React, Tailwind, Node, Next.js, Cloudflare, Firestore, Firebase, and SQL. Bonus points for experience with startup growth from zero to hero.
Additional Information
This is a remote-first role based in Canada with occasional in-person work in our co-working space in downtown Toronto. The salary range is $100,000-$220,000 with competitive equity options, benefits, and unlimited vacation.
Key skills/competency
- Data Aggregation
- API Development
- Python
- Database Management
- Data Parsing
- Financial Data
- AI/LLMs
- Startup Growth
- Remote Collaboration
- Software Engineering
How to Get Hired at Fiscal.ai
🎯 Tips for Getting Hired
- Customize your resume: Tailor skills to Fiscal.ai requirements.
- Highlight data experience: Emphasize API and Python proficiency.
- Showcase project success: Provide measurable impact examples.
- Prepare for technical interviews: Practice coding and data challenges.