Senior Software Engineer ($200-$400K)

How It Works

• 2-minute application
• We reach out, learn what you're building and what excites you, and optimize your profile
• Hiring managers review the cohort and request interviews with candidates they want
• Companies submit competing salary bids directly to you
• You only interview where you're genuinely interested
• Completely free. We have an iMessage agent + humans in the loop you can text anytime w/ questions or requests to help handle scheduling and coordination

Who We're Looking For

• Have built AI-powered products end-to-end, not just prototypes, but systems handling real users
• Can talk fluently about retrieval, memory, agent frameworks, context engineering, eval pipelines and anything else at the cutting edge
• Combine strong software engineering fundamentals with deep awareness of what's happening at the frontier of LLMs and agentic systems
• Thrive in startup environments where the problem is ambiguous and the team is small
• Have 2-8 years of experience, ideally with experience at at least one high-growth company

What Matters to the Companies on Fonzi

• You've worked with LLM APIs in production
• Have opinions on prompt engineering, orchestration patterns, tool-calling, and structured outputs
• Are comfortable across the stack: Python, TypeScript, React, cloud infra (AWS/GCP)
• Understand RAG systems, vector databases, embeddings, and retrieval pipelines
• Built or contributed to eval frameworks. Know how to measure whether an AI system actually works
• Experience with agent frameworks (LangChain, LangGraph, CrewAI), workflow orchestration (Temporal), fine-tuning, or multi-modal systems

What You'll Build

• The companies on Fonzi are working on:
• Agentic systems that automate complex, multi-step workflows across healthcare, legal, fintech, logistics, and compliance
• Production RAG pipelines powering domain-specific knowledge retrieval at scale
• AI-native products where the intelligence layer is the product, not a feature
• Multi-agent orchestration systems with tool-calling, memory, and reasoning capabilities
• Eval and safety infrastructure that makes AI systems trustworthy enough for enterprise deployment
• Full-stack AI applications from MVP to enterprise-grade, serving real customers today

Compensation

$200,000 – $400,000+ base salary depending on experience and role. Many positions include meaningful equity at pre-seed through Series B stage companies.

The Interview Process (Typical)

• Screening conversation looking for communication skills, cultural fit, genuine curiosity about AI
• Technical deep-dive talks on architecture thinking, how you'd design an AI system for a real problem
• Coding or pairing sessions building