> Markdown version of [/jobs/ext/1492134-ai-engineer-remote](https://www.wearedevelopers.com/jobs/ext/1492134-ai-engineer-remote). 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 Engineer - Remote - **Company:** Attercop - **Location:** Brighton and Hove, UK (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Databases, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Django Web Framework, Python (Programming Language), PostgreSQL, NoSQL, Software Engineering, Software Systems, SQL Databases, Data Streaming, Data Logging, Feature Engineering, Data Ingestion, ReactJS, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Fastapi, Data Lakes, AI Platforms, Kubernetes, Machine Learning Operations, Api Design, Restful APIs, Terraform, Data Pipelines, Docker - **Published:** July 30, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=a148c20b80782c52 ## About the Role Experience 2+ years as an AI Engineer or Software Engineer with strong AI/ML exposure Technical Skills Advanced Python (asyncio, type hinting, Pydantic) Backend/API development with FastAPI/Flask/Django Agentic frameworks (LangChain, LangGraph, Microsoft Agent Framework) LLM orchestration, RAG, prompt engineering Cloud (Azure preferred), Docker, Kubernetes IaC (Terraform) PostgreSQL, plus exposure to NoSQL and vector databases CI/CD, monitoring, observability, ML-specific drift detection Collaboration & Communication Work effectively with data scientists, PMs, and stakeholders Communicate technical decisions clearly Maintain strong documentation across pipelines and architectures ## Description You'll design, build, and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering, data science, and MLOps - turning research into robust, scalable, production-ready AI services. Core Responsibilities Model Engineering Build functional AI services from architectural designs Orchestrate data ingestion, inference flows, and output pipelines Optimise latency, memory, and throughput Implement testing, validation, and error/bias analysis Agentic Workflows Design multi-agent systems using LangChain, LangGraph, or Microsoft Agent Framework Implement reasoning loops (e.g., ReAct) Integrate tools, APIs, databases, and memory systems Develop safety and reliability checks for agent behaviour Data Engineering Build scalable ETL/ELT pipelines Perform feature engineering and advanced data prep Integrate SQL/NoSQL, data lakes, warehouses, and streaming APIs Ensure compliance with GDPR/CCPA and internal governance MLOps & Deployment Deploy AI services on Azure using REST APIs Use Docker + Kubernetes for scalable production workloads Build ML-focused CI/CD pipelines Implement monitoring, drift detection, logging, alerting, and retraining Manage infrastructure with Terraform ## Related Videos - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [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) - [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) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) ## 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) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [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 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)