Founding Product Engineer

About the Role

This is a founding-level product engineering role at an early-stage B2B SaaS startup building an AI-driven pricing and monetization platform. You will own entire product modules end-to-end, working directly with customers and leadership to shape architecture, ship production-quality systems, and ensure every feature is drivable by LLM agents. On a small team, your technical judgment and customer-facing scope will have an outsized impact.

What You'll Do

Scope, design, build, and iterate on whole product modules, from versioned APIs to React UI, in close collaboration with customers. Design and evolve architecture for agentic AI systems across Slack bots, terminal interfaces, web, and vendor integrations. Ensure features are drivable by LLM agents via MCP/FastMCP servers and conversational interfaces.

Move pricing and business logic from the client into backend services to preserve financial fidelity. Extend and maintain a typed pricing ontology using Pydantic models covering entities such as SKU, Proposition, Persona, Pricing, Customer, Contract, and Quote. Lead architectural reviews and technical discussions to keep systems robust, extensible, and secure.

Establish testing, observability, deployment, and performance monitoring practices for AI-driven features. Mentor peers, influence product strategy, and help define engineering culture and best practices. Treat money-handling code as load-bearing infrastructure and prioritize thorough root-cause analysis for production issues.

Adopt and improve an AI-native SDLC where agents assist with code generation and automated review gates.

What We're Looking For

8+ years of software engineering experience with proven ownership of product areas at startup or staff-level scope. Deep backend expertise with production experience in FastAPI, Python, and MongoDB or a comparable stack. Credible full-stack range: strong backend depth plus the ability to ship clean, independent React and TypeScript UIs.

Track record of taking ambiguous customer problems all the way to shipped features without a dedicated PM. Experience with B2B SaaS monetization concepts: pricing models, packaging, quoting, billing, or CPQ. Experience building or integrating AI-assisted features and agent-driven workflows, such as LLM-driven interfaces or MCP-like endpoints.

High standards for correctness, especially around financial logic and data integrity. Nice to have: built MCP servers or tooling for LLM agents. Nice to have: experience with billing, CPQ, metering, or pricing systems.

Nice to have: familiarity with data residency, SOC 2, or GDPR-compliant development practices. Nice to have: prior experience as a technical founder or early employee who shipped a 0-to-1 B2B product to paying customers. Must be authorized to work in the United States; visa sponsorship is not available.

Compensation & Benefits Salary range: $200,000 to $250,000 USD annually. Visa sponsorship is not available. Location On-site in San Francisco, CA .

Candidates must be based in San Francisco or willing and able to relocate.

ABOUT THE ROLE

This is a founding-level product engineering role at an early-stage B2B SaaS startup building an AI-driven pricing and monetization platform. You will own entire product modules end-to-end, working directly with customers and leadership to shape architecture, ship production-quality systems, and ensure every feature is drivable by LLM agents. On a small team, your technical judgment and customer-facing scope will have an outsized impact.

WHAT YOU'LL DO

• Scope, design, build, and iterate on whole product modules, from versioned APIs to React UI, in close collaboration with customers.
• Design and evolve architecture for agentic AI systems across Slack bots, terminal interfaces, web, and vendor integrations.
• Ensure features are drivable by LLM agents via MCP/FastMCP servers and conversational interfaces.
• Move pricing and business logic from the client into backend services to preserve financial fidelity.
• Extend and maintain a typed pricing ontology using Pydantic models covering entities such as SKU, Proposition, Persona, Pricing, Customer, Contract, and Quote.
• Lead architectural reviews and technical discussions to keep systems robust, extensible, and secure.
• Establish testing, observability, deployment, and performance monitoring practices for AI-driven features.
• Mentor peers, influence product strategy, and help define engineering culture and best practices.
• Treat money-handling code as load-bearing infrastructure and prioritize thorough root-cause analysis for production issues.
• Adopt and improve an AI-native SDLC where agents assist with code generation and automated review gates.

WHAT WE'RE LOOKING FOR

- 8+ years of software engineering experience with proven ownership of product areas at startup or staff-level scope.

• Deep backend expertise with production experience in FastAPI, Python, and MongoDB or a comparable stack.
• Credible full-stack range: strong backend depth plus the ability to ship clean, independent React and TypeScript UIs.
• Track record of taking ambiguous customer problems all the way to shipped features without a dedicated PM.
• Experience with B2B SaaS monetization concepts: pricing models, packaging, quoting, billing, or CPQ.
• Experience building or integrating AI-assisted features and agent-driven workflows, such as LLM-driven interfaces or MCP-like endpoints.
• High standards for correctness, especially around financial logic and data integrity.
• Nice to have: built MCP servers or tooling for LLM agents.
• Nice to have: experience with billing, CPQ, metering, or pricing systems.
• Nice to have: familiarity with data residency, SOC 2, or GDPR-compliant development practices.
• Nice to have: prior experience as a technical founder or early employee who shipped a 0-to-1 B2B product to paying customers.
• Must be authorized to work in the United States; visa sponsorship is not available. COMPENSATION & BENEFITS Salary range: $200,000 to $250,000 USD annually. Visa sponsorship is not available. LOCATION On-site in San Francisco, CA. Candidates must be based in San Francisco or willing and able to relocate.