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- Tasks: Create innovative AI solutions and enhance internal tools for better productivity.
- Company: Join a forward-thinking company focused on talent engagement and well-being.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real difference in business solutions.
- Qualifications: Experience in AI development, strong Python skills, and cloud engineering knowledge.
- Other info: Collaborative environment with mentorship opportunities and a focus on continuous learning.
The predicted salary is between 36000 - 60000 £ per year.
We help businesses attract, engage, and retain top talent through strategic rewards, recognition, and well-being solutions. As we continue to expand our business, we have an opportunity for a hands-on AI Engineer who is excited about turning real-world challenges into smart, scalable solutions. You will work with the latest third-party AI services, build streamlined workflows and craft high-impact prompts that boost our internal tools, speed up developer productivity and elevate the customer experience.
Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of outcomes and documenting best practices and repeatable patterns.
Manage cloud infrastructure and platform operations, including AWS, Kubernetes, CI/CD pipelines, Terraform, monitoring, performance optimisation, and cost control. Design, develop, and maintain backend services in Python, and contribute to React, TypeScript, and PHP codebases when required.
Lead evaluation and iteration cycles, including defining and tracking offline and online metrics, running A/B tests, meeting latency and cost targets, implementing human-in-the-loop validation, and ensuring robust observability. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies.
Improve internal AI development tooling, including shared libraries, SDKs, and reference implementations for RAG, tracing, prompt management, and evaluation. Contribute to internal enablement and capability-building activities across the organisation.
Partner with Security, Legal, and Data teams to define AI policies, review risks, and ensure privacy, PII protection, and regulatory compliance. Mentor peers, conduct code reviews, and share knowledge to elevate engineering standards across the organisation.
Proven experience in shipping production-grade AI solutions. Applied AI expertise across LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, hybrid search techniques, and effective chunking strategies.
Strong Python as a primary language, with solid testing practices and CI/CD experience; able to contribute when needed in React, TypeScript, and PHP or Node.js. Cloud and platform engineering skills, including AWS, Kubernetes, Docker, infrastructure as code, and modern observability tooling.
Familiarity with LLM tooling ecosystems such as LangChain or LlamaIndex, agentic AI frameworks, vector stores, tracing and logging tools, prompt management platforms, and evaluation frameworks. Strong data engineering capabilities, including dataset creation and validation, ETL development, SQL schema design, and the definition and tracking of meaningful product and model metrics.
Solid understanding of ML fundamentals and experimentation, including metric design, error analysis, model selection, and performance tuning. A strong security and governance mindset, with the ability to communicate clearly with both technical and non-technical audiences, and a high level of ownership from discovery through production and iterative improvement.
Online interview with the Talent Partner and the Director of AI Engineering. Technical interview with Director of AI Engineering, VP of Product Engineering, and VP of Product. If you have any specific requirements or need reasonable adjustments at any stage of the recruitment journey, please let your Talent Acquisition Partner know.
Engineer gezocht in London employer: Reward Gateway
Contact Detail:
Reward Gateway Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineer gezocht in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their products, and be ready to discuss how your skills align with their needs. Practise common technical questions and scenarios related to AI engineering.
✨Tip Number 3
Show off your projects! Whether it's a GitHub repo or a personal website, having a portfolio of your work can really set you apart. Highlight any AI solutions you've built and the impact they had.
✨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, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Engineer gezocht in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI solutions and the specific skills mentioned in the job description. We want to see how your background aligns with our needs!
Showcase Your Projects: Include examples of your previous work, especially any production-grade AI solutions you've shipped. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and skills stand out without unnecessary fluff.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures you’re considered for the role you’re excited about!
How to prepare for a job interview at Reward Gateway
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI concepts, especially around LLMs, RAG architectures, and prompt engineering. Be ready to discuss how you've applied these in real-world scenarios, as this will show your hands-on experience and understanding.
✨Show Off Your Coding Skills
Since Python is a key language for this role, practice coding problems that involve backend services. Familiarise yourself with CI/CD practices and be prepared to demonstrate your ability to contribute to React, TypeScript, or PHP codebases if needed.
✨Understand the Cloud Landscape
Get comfortable with cloud infrastructure, particularly AWS and Kubernetes. Be ready to discuss how you've managed cloud operations and optimised performance in past projects, as this will highlight your technical prowess.
✨Communicate Clearly
You’ll need to explain complex AI concepts to both technical and non-technical audiences. Practice articulating your thoughts clearly and concisely, as effective communication is crucial for collaboration across teams, especially when discussing security and compliance.