Location: Portland, OR (in-office part time) Compensation: $90-120K Experience: 1-3 Years or equivalent ‘proof of work’ and side projects Reports to: CTO The Opportunity Most junior roles involve fixing bugs in legacy systems. This isn't one of them. At Zelody, we are rebuilding financial infrastructure from the ground up using an AI-first approach. We are looking for a hungry, "AI-native" Software Engineer who is obsessed with the potential of LLMs and autonomous agents. You will work directly with our CTO and Principal Architect to turn experimental AI concepts into production-grade financial tools. You’ll build and ship AI-driven workflows that connect APIs, transform data, and automate real financial operations. The Role This is a learn as you go position where your curiosity, work ethic, and drive is as important as your experience and current skillset. You will: Prototype: Rapidly build "proof of concept" features using AI frameworksTest and improve the platform: Work alongside senior mentors to learn how to make AI reliable, secure, and compliant in a regulated banking environment.Ship Production Code: Contribute to our core TypeScript/Node.js stack, ensuring our AI agents play nice with our broader infrastructure. What You Bring (The "AI Mindset") 1–3 years of professional software engineering experience (Fintech experience is a "nice to have," but your ability to build is what matters).A portfolio of "AI Experiments": Whether it’s a side project, a GitHub repo, or a complex automation you built for fun—we want to see Build & Iterate: Develop and refine agentic workflows that handle real-world financial what you’ve tried.Understanding of LLMs: You understand the basics of how LLMs work (tokens, context windows, temperature, and RAG).The "Zelody" Pace: You thrive in a startup environment where things move fast and your work has a direct impact on the company’s success. Technical Stack & Requirements Languages: Experience with TypeScript/Node.js Infrastructure: Some experience with cloud systems like AWS, event-driven architectures.Early Experience with vector databases (Pinecone, Weaviate, etc.).Examples: You’ve built something that uses an LLM to "do" something (execute a tool or call an API), not just "say" something. Why Join Zelody? We are backed by high-conviction funds including Counterpart Ventures and The Fintech Fund. We have revenue, we have product, and we have a massive problem to solve. We’re turning "data noise" into a symphony. If you’re tired of building incremental CRUD apps and want to design the autonomous future of finance, let’s talk.