At a Glance
- Tasks: Build and scale AI-driven products in a dynamic gaming environment.
- Company: Leading digital gaming group with a focus on AI innovation.
- Benefits: Competitive salary, bonuses, pension, and strong learning support.
- Other info: Hybrid working in a vibrant Central London office.
- Why this job: Shape the future of AI in gaming for millions of customers.
- Qualifications: Strong Python skills and hands-on LLM application experience.
About the Company
Our client is a NYSE-listed digital gaming group behind some of the world's best-known sports betting and iGaming brands. Operating across more than 20 countries with close to 3,000 employees, they are one of the largest online gaming businesses in the world, and they are investing seriously in AI across the group. Betting is a real-time, data-heavy business, and they are putting AI to work across the parts of it that matter most: how customers experience the product, how they keep customers safe, and how the business runs day to day.
The Role
We are seeking AI Engineers across all experience levels, from engineers early in their AI career through to senior and lead level, to build and scale AI-driven products across the business. Depending on your level and where you land, that could mean:
- Customer support automation: LLM agents that resolve account, payment and betting queries end to end, with clean handoff to human agents where it counts
- Safer gambling: systems that help spot at-risk behaviour early and deliver the right intervention at the right moment, built to satisfy regulator scrutiny
- KYC, AML and compliance workflows: document understanding and case summarisation that cut manual review time without cutting corners
- Personalisation: relevant content, offers and CRM messaging generated and tested at scale
- Internal tooling: copilots that give trading, CS and compliance teams faster answers from the company's own data
These are applied LLM engineering roles, not quant or pricing roles. You will work closely with senior stakeholders across product, compliance and operations, and own what you ship.
What You'll Do
- Build and deploy production AI applications using LLMs, including agent workflows, tool use and RAG pipelines over company data
- Contribute to evaluation frameworks covering accuracy, latency, cost and reliability, with the extra rigour a regulated industry demands
- Implement retrieval systems from ingestion and chunking through to vector stores and retrieval optimisation
- Ship production-grade code with proper observability, error handling, testing and CI/CD
- Help design guardrails and failure handling so AI systems behave safely with real customers and real money involved
- At senior levels, lead model and framework choices, mentor other engineers and shape how the group builds with AI
What You'll Need
- Strong Python (or TypeScript) and solid software engineering fundamentals
- Hands-on experience building LLM applications or agents, whether in production, at work or through substantial personal projects, with a genuine understanding of their capabilities, limitations and failure modes
- Practical familiarity with RAG architectures, vector databases and prompt engineering
- Exposure to agent frameworks (LangGraph, Claude Agent SDK, OpenAI SDK) or equivalent custom implementations
- An interest in LLM evaluation, debugging and observability
- Cloud platform experience (AWS, GCP or Azure) is a plus at junior level and expected at senior level
The bar scales with the level. For senior roles we will expect production LLM systems shipped and owned end to end. For earlier-career roles we care most about strong engineering fundamentals and real, demonstrable work with LLMs.
Nice to Have
- Experience in a regulated industry (gambling, financial services, insurance) and familiarity with responsible AI, auditability and governance
- Experience with high-traffic, real-time consumer platforms
- Fine-tuning experience and the judgement to know when it beats prompting or RAG
- Observability tooling (LangSmith, Langfuse, W&B) and cost optimisation
- Experience with AI coding tools (Claude Code, Codex, Copilot)
What's on Offer
- Competitive salary benchmarked to your level and experience, plus discretionary bonus
- Pension, employee assistance programme and strong learning and development support
- Genuine production scale: millions of customers, live products, measurable outcomes
- The chance to shape how one of the biggest names in the industry uses AI
- Central London office with hybrid working
AI Engineer in London employer: Parkside
Parkside is an excellent employer that fosters a creative and supportive work culture, perfect for those looking to make a meaningful impact in the e-commerce and social media landscape. With a focus on employee growth and development, you will have the opportunity to take ownership of projects and see your ideas come to life, all while being part of a dynamic team in the vibrant UK market.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Parkside or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Parkside.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Parkside.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Parkside that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Parkside.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Parkside and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Parkside
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Parkside uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
