Software Engineer

Sapiom

📍San Francisco, CA
Posted May 21, 2026
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Job Overview

Position

Software Engineer

Company

Sapiom

Location

San Francisco, CA

Work Type

On-site

Job ID

li-4417435614

Job Description

Location: San Francisco, Ca

About Sapiom
AI agents are beginning to act on behalf of companies and users — making purchases, spinning up compute, triggering workflows, and interacting with third-party systems. But today's financial infrastructure was built for humans, not autonomous systems. Companies and developers need a way to give agents controlled access, meter actions, monetize usage, and transact across rails, without rebuilding payments, risk, and compliance internally.

Sapiom builds the financial payments infrastructure for the machine economy - autonomous spend rails that enable AI agents to transact with real-world services safely, processing every dollar spent, every policy decision navigated, and every risk signal generated.

We have assembled a world-class team with deep payments and infrastructure DNA to build the operating system for machines. Backed by a $15.75M investment from Accel, Menlo, and Anthropic, we are moving with relentless focus to deploy the economic substrate for autonomous agents.

About The Role
This is a high-autonomy engineering role at the intersection of AI and financial infrastructure. You'll design and ship core systems for agentic payments end-to-end, working across the full stack — backend, integrations, platform, and beyond. You'll operate as a true owner, making real technical tradeoffs and shaping product direction alongside the founding team, with AI tools embedded throughout the workflow.

What You Will Do
You'll build core infrastructure and product systems for agentic payments, designing and shipping new capabilities from the ground up. The work spans backend, integrations, platform, and internal systems — moving wherever the problem is. You'll operate with high autonomy, make strong technical tradeoffs, and help scale systems for reliability and performance, all while partnering closely with the founding team on product and engineering direction. AI tools are a first-class part of the workflow here.

Responsibilities

  • Own end-to-end delivery of systems — from design to production — with minimal direction

  • Make pragmatic architectural decisions in ambiguous, fast-moving contexts

  • Move across the stack as priorities shift, without waiting for perfect structure

  • Contribute to product and engineering direction alongside the founding team

  • Scale systems thoughtfully for reliability, performance, and operational speed

Requirements

  • Strong software engineering fundamentals and coding ability

  • High agency and strong product/ownership mindset

  • Systems thinker who can work through ambiguity

  • Comfortable moving across different parts of the stack

  • Bias toward shipping and making pragmatic decisions

  • Actively uses AI-native development tools in their workflow

  • Excited by fast-moving, high-intensity startup environments

Nice to have

  • Experience at high-growth startups

  • Experience building infrastructure, platform, or developer tools

  • Familiarity with AI/ML systems, inference, or agent workflows

  • Experience with payments, APIs, or distributed systems

  • Experience in highly autonomous engineering teams
✦

Interview Prep

AI-powered insights to help you prepare

Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How would you design the architecture for an 'agentic payment rail' that allows an AI agent to autonomously execute transactions while ensuring compliance and risk controls?
  • 2.Sapiom emphasizes using AI-native development tools as a first-class part of the workflow. How do you currently integrate AI tools into your software engineering process, and how have they improved your output?
  • 3.When building distributed systems for financial payments, how do you approach making pragmatic architectural tradeoffs between system reliability, performance, and operational speed in a fast-moving startup?
🎯Behavioral Questions (3)
  • 1.Tell me about a time you had to take ownership of a project end-to-end with minimal direction. How did you figure out what to build, and what was the outcome?
  • 2.Describe a situation where priorities shifted suddenly and you had to move across a different part of the stack or domain. How did you adapt and deliver?
  • 3.Give an example of a time you had to make a pragmatic engineering decision under tight time pressure, knowing it wasn't the 'perfect' architectural solution. How did you decide what to compromise on?
🧩Situational Questions (2)
  • 1.You are tasked with building a new integration with a third-party payment provider, but their API documentation is severely outdated and ambiguous. You need to ship this integration by the end of the week. What is your approach?
  • 2.An AI agent is triggering an unexpectedly high volume of micro-transactions that are passing your current risk policies, but the aggregate spend is starting to look anomalous. How would you handle this immediate system behavior?

Resume Keywords

Make sure these keywords appear on your resume

Agentic paymentsFull-stack engineeringDistributed systemsAutonomous spend railsAI-native developmentEnd-to-end ownershipPayment infrastructurePragmatic architectureHigh-growth startupRisk and compliance

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