> Markdown version of [/jobs/ext/1336432-backend-engineer-ai-job](https://www.wearedevelopers.com/jobs/ext/1336432-backend-engineer-ai-job). 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). --- # Backend Engineer, AI job - **Company:** Artemis Consultants - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Debugging, Distributed Systems, Python (Programming Language), Node.Js, NoSQL, Open Source Technology, SQL Databases, Data Logging, Pytorch, Large Language Models, Backend, Kubernetes, Low Latency, Machine Learning Operations, Front End Software Development, Docker - **Published:** July 18, 2026 - **Apply:** https://jobs.diversity.com/career/2419380/backend-engineer-ai ## About the Role * Strong backend engineering fundamentals in production environments. * Experience running high-throughput, low-latency services. * Familiarity with AI inference patterns (LLMs, embeddings, multimodal). * Comfortable debugging distributed systems under load. * Bias toward shipping and learning from production behavior. TECH STACK: * Python * NodeJs * Pytorch * OpenAI / Anthropic / open-source LLMs * SQl & noSQL * Kubernetes * Docker, * Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput. * APIs are stable, clear, and support seamless integration with frontend and ML systems. * Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact. * Iterative improvements based on real usage continuously increase system performance and reliability. ## Description As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience., * Build and operate backend systems that serve AI-powered features in production. * Design inference pipelines, orchestration layers, and service boundaries around models. * Own production concerns: monitoring, logging, alerting, and incident response. * Optimize latency and throughput across inference, caching, batching, and streaming. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [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) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)