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# Senior Software Engineer

- **Company:** Wintermeyer Ventures
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $230,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Code Review, Cursor, Programming Tools, Python (Programming Language), Natural Language Processing, Node.Js, Software Engineering, TypeScript, ReactJS, Large Language Models, AI Coding Agents, Backend, Build Management, Information Technology, Front End Software Development, Claude
- **Published:** October 27, 2026
- **Apply:** https://www.thejobnetwork.com/job/c99befc2-e559-4354-843e-af08fad5dab0/senior-software-engineer

## About the Role

* Three to six years of software engineering experience, including hands-on system design, architecture, and coding.
 * Experience leading a production platform or core service end to end, with clear ownership of architecture decisions and tradeoffs.
 * Recent experience shipping LLM or agentic AI features to production users.
 * Strong production experience with TypeScript and Node.js or Python, plus familiarity with JavaScript and React.
 * Experience at an early- to growth-stage startup or a large technology company, with a track record of sustained ownership.
 * Daily use of modern AI development tools, such as Claude or Cursor, and a degree in computer science or a related STEM field.
 * Conversational or voice AI, NLP, fintech, banking, regulated financial services, or founding-engineer experience is a plus.

## Description

* Design and build scalable, observable, maintainable platform services for AI-driven financial products.
 * Own architecture, APIs, data models, performance, and security decisions from design through delivery.
 * Build backend systems with TypeScript and Python, and contribute to frontend experiences using JavaScript and React.
 * Take LLM and agentic AI features from design to production, balancing latency, reliability, cost, and scale.
 * Work closely with engineering, product, design, and data partners to turn product priorities into shipped systems.
 * Set engineering standards for code review, testing, deployment, and incident response, and use AI coding tools in daily development.