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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Backend Engineer, AI (Agent Systems) - **Company:** BJAK - **Location:** Greater London, UK - **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:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815170086-backend-engineer-ai-agent-systems ## 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., * 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. Tech Stack * Python * NodeJs * Pytorch * OpenAI / Anthropic / open-source LLMs * SQL & noSQL * Kubernetes * Docker ## Description About the Role A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. 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. You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. Focus * 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. Ideal Experiences * 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. Outcomes * 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. Tech Stack * Python * NodeJs * Pytorch * OpenAI / Anthropic / open-source LLMs * SQL & noSQL * Kubernetes * Docker How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product. ## Related Videos - [Inside Bitpanda's Tech Stack: Scaling a European Fintech Leader - Markus Dorner](https://www.wearedevelopers.com/videos/1979-inside-bitpanda-s-tech-stack-scaling-a-european-fintech-leader-markus-dorner) - [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) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [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 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)