AI Analyst/Engineer

AI Analyst/Engineer

Full-Time 160000 - 160000 £ / year (est.) No home office possible
Orbis Group

At a Glance

  • Tasks: Identify AI use cases, build prototypes, and drive adoption across teams.
  • Company: Dynamic company focused on AI innovation and business evolution.
  • Benefits: Competitive salary up to £160k, 30% bonus, and London-based office.
  • Other info: Blend of technical work and problem-solving with ownership from idea to adoption.
  • Why this job: Shape AI strategy and make a real impact in a high-visibility role.
  • Qualifications: 6–8 years in engineering or technical roles, with AI experience.

The predicted salary is between 160000 - 160000 £ per year.

What you’ll be doing:

  • Identify and shape AI use cases across the business
  • Work directly with stakeholders to understand workflows and inefficiencies
  • Build POCs / prototypes and support production rollout
  • Drive adoption of AI tools across teams
  • Train end users and help embed AI into how people work

What they’re looking for:

  • 6–8 years’ experience across engineering, product, or technical BA-type roles
  • 2–3 years working with AI / LLM / agentic tooling in a practical setting
  • Strong communication skills, able to work closely with non-technical users
  • Experience delivering solutions end-to-end, not just contributing in a silo

Tech-wise: they’re a Microsoft .NET / C# environment, but the stack isn’t the focus here. Python backgrounds are equally relevant.

Why it’s interesting:

  • High visibility role with direct impact on how the business evolves
  • Blend of technical work and real business problem solving
  • Opportunity to shape AI strategy rather than just execute tickets
  • Still hands-on, but with ownership from idea through to adoption

Package:

  • Base up to £160k
  • Bonus 30%+
  • London based, 5 days in office

If you’ve been using AI in a meaningful way and want a role where you can actually shape how it’s applied across a business, then please reach out.

AI Analyst/Engineer employer: Orbis Group

As an AI Analyst/Engineer at our London office, you'll be part of a dynamic team that values innovation and collaboration. We offer a competitive salary package, including a generous bonus structure, and a vibrant work culture that encourages professional growth and the opportunity to shape our AI strategy. Join us to make a tangible impact on the business while working in a supportive environment that fosters creativity and teamwork.
Orbis Group

Contact Detail:

Orbis Group Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land AI Analyst/Engineer

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that AI Analyst/Engineer role.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, prototypes, or any POCs you've built. We want to see how you’ve tackled real-world problems and driven adoption of AI tools. This will make you stand out when you apply through our website.

✨Tip Number 3

Prepare for those interviews! Brush up on your communication skills, especially when explaining complex AI concepts to non-technical users. We need to demonstrate that you can bridge the gap between tech and business effectively.

✨Tip Number 4

Be proactive! Don’t wait for job postings to come to you. Reach out directly to companies you’re interested in, including us at StudySmarter. Express your passion for AI and how you can contribute to shaping their strategy.

We think you need these skills to ace AI Analyst/Engineer

AI Use Case Identification
Stakeholder Engagement
Workflow Analysis
Prototyping
Production Rollout Support
AI Tool Adoption
End User Training
Microsoft .NET
C#
Python
Communication Skills
End-to-End Solution Delivery
Technical Problem Solving
Experience with AI / LLM / Agentic Tooling

Some tips for your application 🫡

Show Your AI Passion: When you're writing your application, let your enthusiasm for AI shine through! Share specific examples of how you've used AI tools in your previous roles and the impact they had. We love seeing candidates who are genuinely excited about shaping AI strategies.

Tailor Your Experience: Make sure to highlight your relevant experience in engineering, product, or technical BA roles. We want to see how your background aligns with the job description, so don’t be shy about showcasing your 6-8 years of experience and any hands-on work with AI or LLMs.

Communicate Clearly: Strong communication skills are key for this role, especially when working with non-technical users. In your application, demonstrate your ability to explain complex concepts simply. We appreciate clarity and a friendly tone!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter team!

How to prepare for a job interview at Orbis Group

✨Know Your AI Stuff

Make sure you brush up on your knowledge of AI, LLMs, and agentic tooling. Be ready to discuss specific use cases you've worked on and how they impacted the business. This shows you’re not just familiar with the tech but can also apply it effectively.

✨Communicate Like a Pro

Since this role involves working closely with non-technical users, practice explaining complex concepts in simple terms. Think about examples where you’ve successfully communicated technical ideas to stakeholders and how that helped drive projects forward.

✨Showcase Your End-to-End Experience

Prepare to talk about projects where you’ve taken solutions from idea to adoption. Highlight your role in each stage and how you ensured successful delivery. This will demonstrate your ability to work across teams and manage the entire process.

✨Be Ready to Problem-Solve

Expect questions that assess your problem-solving skills. Think of scenarios where you identified inefficiencies and implemented AI solutions. Show how you approached these challenges and the impact your solutions had on the workflow.

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