> Markdown version of [/jobs/ext/2729563-back-end-engineer](https://www.wearedevelopers.com/jobs/ext/2729563-back-end-engineer). 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). --- # Back-end Engineer - **Company:** Magentic - **Location:** UK - **Experience:** Expert - **Salary:** £115,000.0 - £125,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, User Authentication, Microsoft Azure, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Software Debugging, Graph Database, Python (Programming Language), Open Source Technology, Queueing Systems, SAP (Applications), Data Streaming, TypeScript, File Transfer Protocol (FTP), Enterprise Software Applications, Large Language Models, Backend, Build Management, Apache Kafka, Graphql, Restful APIs, Oracle Erp, Terraform, Data Pipelines, Docker - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/back-end-engineer-magentic-company-8368705 ## About the Role * Have 6+ years of professional software-engineering experience. * Are fluent in Python and comfortable in TypeScript/JavaScript. * Have built and operated data-intensive systems (batch & streaming) in a cloud environment (AWS, GCP, or Azure). * Know your way around relational, columnar, and KV/graph databases - and when to use which. * Have integrated with real-world enterprise stacks - authentication, SSO, legacy ERPs, message queues, ETL tools. * Can take a loosely defined problem, sketch an architecture, and deliver a production-ready solution in weeks, not months. * Communicate clearly with both engineers and business stakeholders; you enjoy hopping on a customer call to debug an API contract. * Thrive in an early-stage, high-ownership environment - prototype today, deploy tomorrow, iterate next week. Bonus Points * Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience. * Familiarity with supply-chain, procurement, or manufacturing domains. ## Description We are looking for brilliant engineers to join our team at Magentic. We're pushing the boundaries of AI with next-generation agentic systems that can manage entire workflows. We're focusing on a three trillion dollar market of supply chains and procurement. Our mission is to make global manufacturing supply chains robust to an ever-changing world, and to harness the potential of generative AI through thoughtful deployment, maximising benefits while prioritising ethical use and safety. You'll own full-stack features end-to-end, with a focus on building for enterprise data requirements. You will collaborate closely with customer teams to architect and implement sophisticated data pipelines and APIs, directly fueling our cutting-edge agentic AI with terabytes of real-world supply chain data. You will be instrumental in shaping solutions for enterprise clients, all while learning and growing your AI skills in a truly AI-first company at the forefront of agentic systems. What You'll Do * Design & build scalable, performant backend services and data pipelines + written in Python and deployed with Docker & Kubernetes. * Integrate with enterprise ecosystems - enterprise software systems such as SAP and Oracle ERP, GraphQL/REST APIs, SFTP feeds, and event buses (Kafka, Pulsar). * Wrangle large, heterogeneous data sets - model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced workloads * Develop enterprise-level next generation AI systems with the support of Magentic's AI specialists * Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training. * Collaborate directly with executives & operators - run white-boarding sessions, turn ambiguous requirements into concrete specs, demo weekly, and iterate fast. * Champion observability & reliability - instrument services with OpenTelemetry, define SLIs/SLOs, and automate incident response. * Contribute across the stack - build lightweight front-ends when needed and pair with ML engineers on inference and evaluation pipelines. ## Related Videos - [Engineering Mindset in the Age of AI - Gunnar Grosch, AWS](https://www.wearedevelopers.com/videos/1735-engineering-mindset-in-the-age-of-ai-gunnar-grosch-aws) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Meet Your New BFF: Backend to Frontend without the Duct Tape](https://www.wearedevelopers.com/videos/682-meet-your-new-bff-backend-to-frontend-without-the-duct-tape) - [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) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [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 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)