> Markdown version of [/jobs/ext/3030650-ai-software-engineer-backend-sf](https://www.wearedevelopers.com/jobs/ext/3030650-ai-software-engineer-backend-sf). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Software Engineer, Backend (Sf - **Company:** VISUAL HISTORY OF BUILDINGS BEING BUILT, LLC - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $145,000.0 - $205,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Amazon Web Services, Code Review, Cursor (Graphical User Interface Elements), Elasticsearch, Design of User Interfaces, Human-Computer Interaction, PostgreSQL, Machine Learning, Node.Js, Prism (Software), Redis, Software Engineering, TypeScript, Unstructured Data, ReactJS, Large Language Models, Prompt Engineering, Backend, Juniper, Webpack, AI Platforms, AWS Fargate, Apache Kafka, Graphql, Data Management, Front End Software Development, NestJS, Data Pipelines - **Published:** September 22, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-software-engineer-backend-sf-san-francisco-ca--74ee6466-e15d-46e1-b5e0-62ed25160872 ## About the Role * Work in the SF office 4+ days a week. * Two years of software engineering experience. * Experience with TypeScript and tools such as GraphQL, Relay, React, and Node.js. * Experience working at early-stage companies where you shipped products end-to-end and wore many hats. * Excited to build with AI and apply it to real customer problems. No prior AI or machine learning background is required; you will learn our AI stack here. Under the Hood * Infrastructure: AWS, CDK, Fargate ECS * Backend: TypeScript, Node.js, Prisma, NestJS, PostgreSQL, Kafka, Redis, Elasticsearch, GraphQL * Frontend: TypeScript, React, Relay, Ant Design, Vite, GraphQL * AI: LLMs, prompt engineering, agentic workflows, and Loop's internal AI platform, Amazon Web Services (AWS), Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Automation, Billing, Code Reviews, Compensation and Benefits, Cross-Functional, Customer Support/Service, DNA, Data Management, Documentation, Engineering, GraphQL, Investment Capital, Juniper Networks M-Series, Logistics, Machine Learning, Node.js, Product Design, Product Development, Product Shipments, Productivity Management, React.js, Relay, Sales, Software Development, Software Engineering, Supply Chain, Technical Delivery, Technical/Engineering Design, Unstructured Data, User Interface/Experience (UI/UX) ## Description As an AI backend engineer, you will work closely with founders and customers to understand and solve their logistics billing and payment pain points. You will ship features that directly impact customers, and you will do it with AI in two ways: building products with AI, and building the systems that let AI agents and non-technical users deliver technical work that used to require an engineer. The most valuable work here solves a whole category of problems rather than a single one-off feature. You will face and solve many complex technical challenges while you receive guidance and feedback from the team. You will shape the Loop DNA and define how we grow as a company. Responsibilities * Work cross-functionally with product, design, and sales to understand requirements and ship thoughtful solutions. * Build and ship the AI harness: the data pipelines, schemas, validation, and feedback loops that let agents do work reliably at scale. * Start from the outcome, not the process: curate the harness, data, and success criteria instead of the specific logic, then let agents write and validate it against real data. * Write high-quality code optimized for extensibility, working across component boundaries from frontend to backend, infrastructure, and our AI stack. * Engage in code reviews to maintain a high bar of engineering excellence. * Lead discussions and documentation to communicate and arrive at the best technical design. * Adopt AI technologies such as Cursor/Codex/Claude to accelerate software development and champion adoption of AI tools across the organization for increased productivity. * Promote better practices, share technical knowledge, and help grow Loop through deliberate feedback on product, process, and culture. ## Related Videos - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [The AI-Ready Stack: Rethinking the Engineering Org of the Future](https://www.wearedevelopers.com/videos/1706-the-ai-ready-stack-rethinking-the-engineering-org-of-the-future) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [Next, Nest, Nuxt… Nust?](https://www.wearedevelopers.com/videos/421-next-nest-nuxt-nust) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)