At a Glance
- Tasks: Unlock AI-driven solutions and deploy cutting-edge technology to transform business processes.
- Company: Join Moneybox, an award-winning wealth management platform with a mission to empower everyone.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and creativity.
- Why this job: Be at the forefront of AI innovation and make a real impact on customer experiences.
- Qualifications: Experience in deploying production-grade LLM systems and strong Python skills.
The predicted salary is between 81000 - 99000 £ per year.
All potential candidates should read through the following details of this job with care before making an application.
hackajob is partnering directly with Moneybox to hire for this role.
About Moneybox
At Moneybox, our mission is to give everyone the means to get more out of life.
We're guided by our belief that wealth isn't about the money, it's about the means to more - more freedom, opportunities, possibilities, and peace of mind.
Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether theyre saving and investing, buying their first home, or planning for retirement.
Job Brief
Moneybox serves more than 2M customers and runs a live service handling over 20M API requests a day.
We have agreed a company-wide AI Platforms strategy and are building a new AI Deployment team to deliver on it.
This is the first of several Senior AI Deployment Engineer hires, reporting to the Head of AI Platforms & Deployment.
You will be a forward-deployed senior engineer who unlocks AI-driven solutions to business problems: an expert in deploying AI and using it safely, not an ML modeller.
The work is mainly Python across the modern AI engineering stack - harness engineering, skills and tool building, agent workflows and orchestration, agent hosting and sandboxing, guardrails, evals, RAG and context engineering, and tokenomics (cost, latency, model selection).
Production-grade LLM system experience is the core requirement.
You will work on three types of project
- Departmental engagements.
Embed with departments to AI-enable tasks and processes in a more sophisticated way than "just ask Claude" - for example, Python pipelines where one step is an LLM API call - delivering real incremental value with each engagement and transforming working patterns into load-bearing, AI-enabled business processes.
- Customer-facing AI deployment.
Deploy and integrate AI components built by our ML and Decisioning teams into production: the engineering implementation layer between a working model and a live customer feature.
- AI platform capabilities. xgikmsk Work with the AI Platforms team to turn engagement patterns into safe, increasingly self-serve company-wide tooling.
Departments across Moneybox are already building AI tools themselves - we want to provide them with a safe path to load-bearing use at sca
Please click on the apply button to read the full job description
Senior AI Deployment Engineer in London employer: Hackajob
Joining Google as a Security Platform Engineer in the UK Public Sector means becoming part of a dynamic and innovative team dedicated to delivering secure private cloud services for critical customers. With a strong emphasis on employee growth, you will have access to cutting-edge technology and collaborative opportunities that foster professional development. The inclusive work culture at Google encourages creativity and teamwork, making it an exceptional employer for those seeking meaningful and impactful work in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Deployment 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 Hackajob 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 Hackajob.
✨Tap into Online Developer Communities
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✨Explore Job Boards Specifically for Tech Roles
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We think you need these skills to ace Senior AI Deployment 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 Hackajob.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Hackajob 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 Hackajob
✨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 Hackajob 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.
