Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Deploy and maintain AI tools to transform client services and enhance operational efficiency.
- Company: Citation Group, a leading innovator in AI solutions for professional services.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Why this job: Join a pioneering team reshaping the future of AI in professional services.
- Qualifications: Experience with AWS and AI deployment; strong communication skills are essential.
- Other info: Dynamic remote work environment with a focus on impactful AI initiatives.
The predicted salary is between 36000 - 60000 £ per year.
Overview
We're Not Just Talking About AI. We're Doing It. Citation Group won the National AI Awards 2025 for AI Innovation. We've deployed AI agents that are genuinely transforming how 120,000+ clients receive compliance and HR support. Our AI initiatives have delivered recognised business benefits and we're just getting started. Now we need someone to take it further.
The Role
We're looking for an AI Deployment Engineer to join our growing AI team and help us move from proof-of-concept to production-at-scale across initiatives that will genuinely change how services are delivered.
What This Role Exists
Our Employment Law Team handles thousands of client emails weekly. Currently, advisors spend significant time on triage, categorisation, and drafting responses for routine queries — time that should be spent on complex, high-value advice. We're building AI-powered email triage and response drafting to transform this. This is the first initiative in a broader transformation programme that will establish the pattern for how AI agents and human advisors work together: agents translate and prepare, humans validate and deliver. This role will be instrumental in making that happen — and then scaling the same model across our H&S, Food Safety, and ISO businesses.
Where We Are on Our AI Journey
This isn't a startup experimenting with AI. We've been executing:
- Commercial Acceleration programme live — AI-powered lead enrichment and sales intelligence
- AI Champions programme running across UK, Canada, and Australia
- 11+ AI product features planned across iHasco, HR Atlas, and H&S platforms
The Roadmap You'll Help Deliver
Our transformation spans multiple strategic pillars. As AI Deployment Engineer, you'll be pivotal to:
- Service Excellence: Email triage and auto-drafting for Employment Law → expanding to audit automation, appointment scheduling (reducing 400 calls to 80 appointments), and document generation
- Commercial Acceleration: Supporting AI-powered lead enrichment, signal detection, and sales intelligence systems
- Product Differentiation: AI features across iHasco, HR Atlas, and H&S platforms that set us apart from competitors
What You'll Do
- Deploy, maintain, and monitor AI tools and applications — you're the bridge between experimentation and production
- Build and deploy lightweight POCs using LLMs, RAG pipelines, and API integrations
- Work with AWS services to configure, deploy, and troubleshoot AI pipelines
- Scale solutions across multiple brands and geographies (UK, Canada, Australia)
- Collaborate with data scientists and non-technical stakeholders to bring AI tools to life
- Create documentation that ensures solutions are sustainable and well-understood
- Communicate progress and demo AI capabilities to stakeholders across the business
What We're Looking For
Must-Haves
- Hands-on experience with AWS (Cloud Practitioner level or higher)
- Working knowledge of LLMs, prompt engineering, and modern AI deployment practices
- Experience deploying or managing AI tools in production environments
- Ability to work across build and operational contexts — not just R&D
- Strong communication skills — you can explain technical concepts to non-technical users
- A problem-solver who self-starts, spots opportunities, and asks 'how can we make this better?'
Nice-to-Haves
- Experience with RAG pipelines, LLMOps, or model monitoring
- Familiarity with Databricks, Salesforce integrations, or data pipelines
- Interest in the intersection of LLMs and enterprise data systems
What This Role Isn't
This is not a pure R&D or data science role. You won't be training models from scratch or leading architecture strategy. You'll be deploying, adapting, and embedding existing AI capabilities — making them useful, stable, and scalable across the business.
The Details
- Location: Remote (UK-based)
- Reports to: Head of Data Science and AI
- Level: Mid-Level
- Salary: Competitive (to be confirmed)
Join Us
Citation Group is a £280M+ PE-backed business serving 120,000+ clients across UK, Canada, and Australia. We're not talking about AI transformation — we're living it. If you want to be part of a team that's genuinely reshaping how professional services are delivered through AI, we want to hear from you.
AI Deployment Engineer in London employer: The Citation Group
Contact Detail:
The Citation Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Deployment Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those at Citation Group. A friendly chat can open doors and give you insights that a job description can't.
✨Tip Number 2
Show off your skills! Prepare a mini-project or a demo that highlights your experience with AWS and AI deployment. This hands-on approach can really impress during interviews.
✨Tip Number 3
Be ready to discuss real-world applications of AI. Think about how you've solved problems in past roles and be prepared to share those stories. It shows you're not just book-smart but also practical.
✨Tip Number 4
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 AI Deployment Engineer in London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI shine through! We want to see how excited you are about deploying AI tools and making a real impact. Share any relevant projects or experiences that highlight your passion.
Tailor Your Application: Make sure to customise your application to fit the AI Deployment Engineer role. Highlight your hands-on experience with AWS and any knowledge of LLMs or AI deployment practices. We love seeing candidates who take the time to align their skills with our needs!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and experiences. Remember, we’re looking for someone who can communicate complex ideas simply, so show us you can do just that!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at The Citation Group
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI deployment practices, especially around LLMs and AWS. Be ready to discuss how you've used these technologies in past projects, as this role is all about taking AI from proof-of-concept to production.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your ability to identify problems and implement solutions. This role requires a proactive mindset, so think of times when you've spotted opportunities for improvement and how you acted on them.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. You might want to prepare a few scenarios where you successfully communicated technical details to a non-technical audience.
✨Demonstrate Collaboration
This position involves working closely with data scientists and other teams. Think of examples where you've collaborated effectively in the past, and be ready to discuss how you can bridge the gap between technical and operational contexts.
