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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML Engineer - **Company:** Cloudwick UK Limited - **Location:** Bromley, UK - **Experience:** Expert - **Salary:** £80,000.0 - £95,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Continuous Delivery, Continuous Integration, Identity and Access Management, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Next.js, Systems Architecture, TypeScript, Web Application Frameworks, AWS Cdk, ReactJS, System Availability, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Fastapi, Vue.js, Information Technology, Machine Learning Operations, Front End Software Development, Terraform, Network Server, Microservices - **Published:** September 27, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=702b1db3dc90176a ## About the Role Experience: 6-8 years (1-2 years with AI tools and technologies), The role requires a blend of senior technical depth, system architecture capability, and strong product sense, including: * Strong full-stack engineering skills, combining advanced Python (FastAPI, testing, typing) for the backend with proven experience in modern JavaScript/TypeScript front-end frameworks (React, Next.js, etc.) for building AI-driven UIs. * Deep, hands-on experience with AWS AI/ML ecosystems (Amazon Bedrock, Amazon SageMaker model endpoints, pipelines, AWS OpenSearch) and agent orchestration frameworks (e.g., LangChain, LangGraph, ADK). * Solid understanding of MLOps and CloudOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring on AWS. * Proven experience architecting, deploying, and operating complex ML systems in production (batch and real-time). * Advanced familiarity with RAG architectures, prompt engineering, AI guardrails, and LLM evaluation techniques. * Previous experience developing agentic capabilities, such as custom agent skills, MCP servers, and LLM tool usage. * Strong grasp of security, privacy, and governance principles, particularly AWS IAM, Secrets Manager, and PII handling. * Effective communication skills with the ability to translate complex AI concepts to non-technical stakeholders and advocate for UX/UI best practices. * Bachelor's or Master's degree in Computer Science/Engineering/related field, or demonstrable equivalent experience. In addition to the above, we would LOVE if you have: * AWS Certifications (e.g., AWS Certified Machine Learning - Specialty, AWS Certified Solutions Architect). * Knowledge of advanced vector databases (Pinecone, Weaviate, Qdrant) and retrieval strategies. ## Description The role covers the full AI/ML engineering lifecycle, from discovery and back-end deployment to front-end user experience and monitoring. Responsibilities include: * Designing and implementing full-stack agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on an AWS-first stack. * Building intuitive front-end interfaces (using modern frameworks like React, Vue, or Next.js with TypeScript/JavaScript) to seamlessly integrate generative AI features and chat interfaces into internal tooling and customer-facing products. * Developing robust back-end APIs and microservices (Python, FastAPI) for AI/ML solutions, ensuring security, high availability, scalability, and observability. * Building and maintaining production ML pipelines and services on AWS for non-GenAI use cases (e.g., recommender systems, customer segmentation models, leveraging supervised, unsupervised, and/or econometric modelling). * Implementing CI/CD for ML services and full-stack applications, writing infrastructure as code (Terraform, AWS CDK), and monitoring for system latency, model/data drift, and performance. * Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and strict compliance with privacy regulations. * Mentoring mid-level/junior engineers and contributing to reusable components, architectural documentation, and engineering best practices that improve AI/ML delivery across the organisation. * Collaborating closely with data engineers, data scientists, UX/UI designers, and product managers to deliver impactful, end-to-end solutions. * Driving the evaluation of new AWS AI technologies, frameworks, and tooling, contributing architectural recommendations for continuous improvement and "build vs. buy" decisions. ## Related Videos - [Build your backend using FastAPI](https://www.wearedevelopers.com/videos/506-build-your-backend-using-fastapi) - [Exploring LLMs across clouds](https://www.wearedevelopers.com/videos/1457-exploring-llms-across-clouds) - [Lessons learned from building a thriving Vue.js SaaS application](https://www.wearedevelopers.com/videos/1666-lessons-learned-from-building-a-thriving-vue-js-saas-application) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [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) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) ## 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 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)