Software Engineer | On-site | San Francisco
Team: Engineering
Location: San Francisco, California
Commitment: Full Time
Workplace Type: onsite
This is a hands-on technical role where you'll blend solid software engineering fundamentals with a working understanding of large language model behavior. You'll build prompts and tools that deliver consistent, high-quality outputs for backend financial processing. We prefer candidates who can start immediately.
The tech stack
What you'll do:
- Backend Development: Write backend features end to end — data models, business logic, and API integrations that make our product work reliably for customers
- Prompt Engineering: Design, version, and systematically test prompts that drive our backend AI agent's financial reasoning and decision-making — measuring accuracy, consistency, and reliability across diverse inputs
- Data Processing: Build and maintain production tools that process financial data at scale
- Data Analysis: Use SQL and our analytics infrastructure to evaluate prompt performance, scraper reliability, and system behavior
- Shipping to Production: Own your implementations end to end, participate in our CI/CD process, and respond to production incidents as needed
What we're looking for:
- Degree in Computer Science
- Hands-on experience with large language models (GPT, Claude, etc.)
- Strong technical writing and analytical skills with attention to precision and systematic testing methodologies
- Detail-oriented approach to documentation, performance measurement, and systematic experimentation in a fast-paced startup environment
- Ability to work out of our San Francisco office
What you'll gain
- Direct mentorship from experienced engineers and ML researchers with real-world experience building production AI systems
- Deep technical understanding of prompt engineering for backend financial automation and exposure to enterprise-scale AI infrastructure
- Experience with performance optimization, testing frameworks, and AI system reliability in a production fintech environment
- Competitive compensation
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