At a Glance
- Tasks: Design and optimise scalable AI platforms for next-gen intelligent products.
- Company: Join a dynamic tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a fast-paced team driving real-world AI solutions.
- Why this job: Shape the future of AI with hands-on engineering in a collaborative environment.
- Qualifications: Experience in cloud infrastructure, Kubernetes, and CI/CD automation.
The predicted salary is between 60000 - 80000 £ per year.
We're hiring an experienced AI Platform Engineer to design, build and operate a production-grade Generative AI platform powering next-generation intelligent products. This is a hands-on engineering role focused on taking AI solutions from prototype to scalable, reliable services used in real-world environments. You’ll sit at the intersection of DevOps, cloud infrastructure and applied AI owning the full lifecycle of Retrieval-Augmented Generation (RAG) and LLM-powered systems across modern cloud architecture. This role is about engineering, not research. You will architect and run the infrastructure that enables AI to perform securely, reliably and at scale ensuring performance, cost control and operational maturity as adoption grows.
You’ll work closely with AI engineers, security teams, and product stakeholders to transform experimental models into hardened, production-ready services while shaping a reusable AI platform capable of supporting multiple products.
What You’ll Be Doing
- Design and optimise scalable RAG pipelines and vector search systems
- Orchestrate multi-model AI services with a focus on latency, resilience and performance
- Productionise GenAI workflows and ensure they operate reliably under real usage
- Build and run AI services across AWS and Databricks
- Develop ingestion, embedding and retrieval pipelines
- Deploy containerised workloads via Kubernetes and Helm
- Implement Infrastructure-as-Code using Terraform
- Introduce end-to-end monitoring, tracing and alerting for AI workloads
- Improve inference and retrieval performance while reducing operational cost
- Establish fault-tolerant, scalable infrastructure patterns
- Embed security, evaluation and governance into the AI lifecycle
- Build CI/CD pipelines and automation to support continuous model deployment
- Create reusable platform components to accelerate future AI initiatives
Strong experience in:
- Cloud infrastructure engineering (AWS-focused environments)
- Kubernetes, containerisation, and distributed systems
- Terraform / Infrastructure-as-Code
- CI/CD, automation, and platform reliability
- Running production workloads with high availability requirements
Plus, experience with one or more of the following:
- MLOps or ML platform engineering
- RAG architectures, embeddings, or vector search
- Model serving, observability or performance optimisation
- Data / AI workflow orchestration in Databricks or similar ecosystems
Why Join?
- Work on real-world AI systems operating at scale
- Own platform design decisions and influence long-term architecture
- Blend modern DevOps practices with cutting-edge Generative AI use cases
- Be part of a growing, innovation-driven engineering environment
- Opportunity to define how AI is operationalised across multiple products
If you’re excited by building the infrastructure that makes AI usable, scalable and reliable in production, we’d love to hear from you.
AI Platform Engineer (DevOps / MLOps Focus). Job in London LilyLifestyle Jobs employer: United Cerebral Palsy of Georgia
At LilyLifestyle, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As an AI Platform Engineer in London, you'll have the opportunity to work on cutting-edge Generative AI systems while enjoying a supportive environment that prioritises employee growth and development. With a focus on real-world applications and a commitment to operational excellence, we empower our team members to take ownership of their projects and shape the future of AI technology.
Contact Details:
United Cerebral Palsy of Georgia Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Platform Engineer (DevOps / MLOps Focus). Job in London LilyLifestyle Jobs
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI platforms, DevOps, or MLOps. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and real-world scenarios. Practice explaining your thought process when tackling problems, as this is key for roles like AI Platform Engineer.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace AI Platform Engineer (DevOps / MLOps Focus). Job in London LilyLifestyle Jobs
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Platform Engineer role. Highlight your experience with cloud infrastructure, Kubernetes, and any relevant MLOps projects to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about building scalable AI platforms. Share specific examples of how you've tackled challenges in previous roles, especially those related to DevOps and AI.
Showcase Your Projects:If you've worked on any relevant projects, whether personal or professional, make sure to mention them! We love seeing real-world applications of your skills, especially in areas like RAG pipelines or CI/CD automation.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at United Cerebral Palsy of Georgia
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS, Kubernetes, and Terraform. Brush up on your experience with CI/CD pipelines and how you've implemented them in past projects. Being able to discuss specific examples will show that you’re not just familiar with the tools but have hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to discuss challenges you've faced in previous roles, particularly around scaling AI solutions or optimising performance. Think of a few scenarios where you had to troubleshoot issues or improve processes, and be ready to explain your thought process and the outcomes.
✨Understand the AI Lifecycle
Since this role involves transforming experimental models into production-ready services, it’s crucial to understand the entire AI lifecycle. Be prepared to talk about how you’ve embedded security and governance into your workflows and how you ensure reliability and performance in real-world applications.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the role and the company. Ask about their current AI projects, the team dynamics, or how they measure success in their AI initiatives. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.
