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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML Engineer - **Company:** The Borough - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Software Quality, Code Review, Software Debugging, Software Design Patterns, DevOps, Github, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Performance Tuning, Software Engineering, Systems Integration, Management of Software Versions, Large Language Models, Multi-Agent Systems, Generative AI, Backend, Fastapi, Information Technology, Machine Learning Operations, Software Version Control, Docker - **Published:** August 18, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/x/44365145/ ## About the Role What we're looking forGreat AI and machine learning capability only creates value once it runs reliably in the real world. This role exists to bridge that final, critical gap-taking the AI/ML solutions developed within our Data Science team from promising prototypes to robust, scalable production systems that our teams and customers depend on every day.Sitting within Data Science, this is at heart a hands-on AI/ML engineering role. Your primary focus will be productionising Generative AI and agentic systems-building the APIs, tools, integrations and workflows that let LLMs, and agents operate reliably at scale. You will also support the broader range of machine learning models and pipelines across the business. You will be the key partner working hand in hand with Engineering, DevOps and Infrastructure teams to bring our models and systems into production-owning the technical journey of making AI/ML systems live, stable, secure and performant.As a senior member of the Data Science team, you will set the standard for production readiness, act as the bridge between data science and the wider engineering organisation, drive delivery across teams, and mentor colleagues. Your work will directly determine how quickly and confidently Argus can bring new AI/ML capabilities to life.What will you be doingDelivery & EngineeringDesign and build robust, secure APIs and backend components that power AI/ML, GenAI and agentic applications.Engineer agentic systems-integrating LLMs with tools, data sources, and business workflows into reliable, production-grade pipelines.Drive systems from prototype to production, owning reliability, scalability, and operational readiness.Raise code quality, structure, and production readiness across the AI/ML stack.Debug and resolve issues across APIs, environments, and integrations, ensuring rapid response times and minimal disruption.Collaboration & PartnershipAct as the primary technical partner between Data Science and the Engineering, DevOps and Infrastructure teams, taking solutions from development through to live deployment.Advise and support colleagues across the business whose systems integrate with AI/ML and agentic components.Proactively resolve technical ambiguity to reduce delivery friction and rework, ensuring a smooth handover from prototype to production.Technical Leadership & EnablementEstablish and evolve engineering standards for productionising AI/ML, including testing, observability, versioning, and release management.Mentor and guide data scientists and engineers, providing code reviews and hands-on technical support.Champion a culture of disciplined engineering, continuous improvement, and operational excellence within Data Science.Skills and ExperienceEducationA degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline-or equivalent hands-on experience. An MSc or PhD is welcome but not essential.Essential Experience & SkillsExceptionally strong Python programming skills, with a deep grasp of object-oriented design, clean code, and core software engineering principles (e.g. SOLID, design patterns, modularity, testability).Strong backend / API engineering experience, ideally in Python (e.g. FastAPI, or similar).Hands-on experience building and operating solutions in AWS environments.Proficiency with Docker, GitHub, and CI/CD pipelines.Proven ability to partner with and work across teams to drive delivery into production.Strong problem-solving, debugging, and performance optimisation skills.Solid software engineering foundations, including version control, automated testing, and monitoring.DesirableExperience building or productionising agentic AI systems-tool use, orchestration, multi-step reasoning, or agent frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, or similar).Experience with GenAI / LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) ## 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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)