AI Engineer - Infrastructure
AI Engineer - Infrastructure

AI Engineer - Infrastructure

Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and deploy cutting-edge AI solutions for top-tier enterprises.
  • Company: Join causaLens, a pioneering tech company transforming the future of work.
  • Benefits: Enjoy 25 days paid holiday, share options, and a great work-life balance.
  • Why this job: Make a real impact by solving business problems with innovative AI technologies.
  • Qualifications: Experience in deploying enterprise-grade AI solutions and strong solution architecture skills.
  • Other info: Dynamic team culture with opportunities for learning and development.

The predicted salary is between 36000 - 60000 ÂŁ per year.

Overview

causaLens delivers Digital Workers that enterprises can truly rely on. Soon, competing without Digital Workers will be impossible. Just as it became unthinkable to manufacture without machines, we’ve built the first factory and Operating System for creating, deploying, and governing Digital Workers. For too long, enterprises have been bogged down by repetitive work, an overload of tools, and costly consultancies.

It’s time to simplify. It’s time for Digital Workers to take on the repetitive workflows, freeing humans to focus on what matters most. Trusted by leading companies like J&J, Cisco, IPG Group, and Syneos Health.

Backed by over $50M in funding from world-class investors, including Molten Ventures (formerly Draper Esprit), Dorilton Capital, and IQ Capital, plus visionary angel investors such as the CEO of Revolut.

Here are 2 articles that define our culture:

  1. A Hiring Framework for a New Kind of Services Company
  2. The Primacy of Winning

Requirements

We’re looking for AI Engineers who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects – designing, building, and delivering intelligent solutions that solve real business problems at scale.

What you’ll bring:

  • Expertise in the deployment of enterprise-grade AI solutions to cloud and on-premise customer environments with a focus on availability, observability and security.
  • Proven track record with at least one of the major cloud providers and an understanding of DevOps best practices.
  • Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows.
  • Client-facing experience with a forward deployed engineering mindset. You’ll work directly with both technical teams and business stakeholders to understand real-world challenges and deliver solutions that drive measurable impact.
  • Strong solution architecture and delivery skills: ability to translate complex business problems into scalable, intelligent AI solutions.

What you’ll do

  • Collaborate directly with top-tier enterprises to understand needs, design and deploy bespoke agentic workflows.
  • Design and implement robust architectures that leverage the latest AI technologies.
  • Lead the delivery of high-impact AI products from concept to deployment.

Benefits

  • 25 days of paid holiday, plus bank holidays
  • carry over/sell holiday options (up to 5 days)
  • Share options
  • Happy hours and team outings
  • Cycle to work scheme
  • Friendly tech purchases
  • Benefits to choose from, including Health/Dental Insurance
  • Special Discounts
  • Learning and development budget
  • Office snacks and drinks

Logistics

Our interview process consists of screening sessions with the hiring manager and a \”Day 0\” which involves an approximately 3-hour in-person challenge followed by an in-person presentation and interviews. Have questions? We encourage open dialogue—reach out anytime.

If you require accommodations during the application process or in your role at causaLens, please contact us at talent@causalens.com

Seniority level

  • Associate

Employment type

  • Full-time

Job function

  • Software Development

Industries

  • Software Development

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AI Engineer - Infrastructure employer: causaLens

At causaLens, we pride ourselves on being an exceptional employer that values innovation and employee well-being. Our vibrant work culture fosters collaboration and creativity, allowing AI Engineers to engage in meaningful projects that drive real impact for leading enterprises. With generous benefits such as 25 days of paid holiday, a learning and development budget, and opportunities for personal growth, we ensure our team members thrive both professionally and personally in a supportive environment.
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Contact Detail:

causaLens Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land AI Engineer - Infrastructure

✨Tip Number 1

Get to know causaLens and its culture before your interview. Dive into their articles and understand their vision for Digital Workers. This will help you connect your skills with their mission during the conversation.

✨Tip Number 2

Prepare to showcase your hands-on experience with AI solutions. Think of specific projects where you've deployed enterprise-grade AI, and be ready to discuss the challenges you faced and how you overcame them.

✨Tip Number 3

Practice explaining complex technical concepts in simple terms. You’ll be working with both technical teams and business stakeholders, so being able to bridge that gap is key to landing the job.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive about their job search.

We think you need these skills to ace AI Engineer - Infrastructure

AI Solutions Deployment
Cloud Computing
DevOps Best Practices
Production-Grade Solutions
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAGs)
Multi-Cloud Platforms (MCPs)
Agentic Workflows
Client-Facing Experience
Solution Architecture
Scalable AI Solutions
Collaboration with Technical Teams
Business Stakeholder Engagement
Impact Measurement

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with cloud providers and any hands-on projects you've worked on that relate to deploying AI solutions. We want to see how your skills match what we're looking for!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can help enterprises simplify their workflows. We love seeing genuine enthusiasm, so let your personality come through!

Showcase Your Projects: If you've worked on any relevant projects, make sure to include them in your application. Whether it's building production-grade solutions or client-facing experiences, we want to know how you've tackled real-world challenges with your skills.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at causaLens!

How to prepare for a job interview at causaLens

✨Know Your AI Stuff

Make sure you brush up on your knowledge of AI technologies, especially LLMs and agentic workflows. Be ready to discuss how you've deployed enterprise-grade AI solutions in the past and how you can apply that experience to causaLens' projects.

✨Understand Their Culture

Read up on the articles provided about causaLens' culture. Understanding their hiring framework and values will help you align your answers with what they’re looking for, showing that you’re not just a fit for the role but also for the company.

✨Prepare for Real-World Scenarios

Since the interview includes a practical challenge, think about real business problems you've solved with AI. Prepare to explain your thought process and how you translated complex issues into scalable solutions during your previous roles.

✨Engage with Questions

Don’t hesitate to ask questions during the interview. This shows your interest in the role and helps you understand how you can contribute to causaLens. Think about what you want to know regarding their projects, team dynamics, and future goals.

AI Engineer - Infrastructure
causaLens
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