At a Glance
- Tasks: Build secure and scalable cloud infrastructure for AI and ML workflows.
- Company: Join Faculty, a leader in responsible AI innovation since 2014.
- Benefits: Enjoy unlimited annual leave, private healthcare, and flexible working options.
- Why this job: Shape the future of AI while making a real impact in healthcare.
- Qualifications: Experience with major cloud providers and Infrastructure as Code, especially Terraform.
- Other info: Diverse team culture that values intellectual curiosity and positive impact.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then we’ve worked with over 350 global customers to transform their performance through human‑centric AI. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle – and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business and reputation is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
Bringing medicine to patients is complex, expensive and high‑risk. Faculty’s Life Sciences team is concentrated on building AI solutions which optimise the research and commercialisation of life‑changing therapies. We partner with major pharma firms, academic research centres and MedTech start‑ups to design and deliver solutions which address critical healthcare challenges and help to democratise health for all.
We’re looking for a Cloud Engineer to build the backbone of applied artificial intelligence for our customers. You will design, build and deploy robust, secure and scalable cloud infrastructure that powers cutting‑edge data and machine‑learning workflows. Working in a cross‑functional team you’ll solve complex challenges and empower our data scientists and ML engineers to deploy their work effectively, shaping the future of AI solutions.
What you’ll be doing:
- Building robust, secure and scalable cloud infrastructure for AI and ML workflows.
- Partnering with technical and non‑technical stakeholders from initial idea generation through to implementation and shipping.
- Enabling Machine Learning Engineers and Data Scientists by contributing to internal best‑practice standards and reusable code repositories.
- Proactively identifying and recommending new ways customers can leverage cloud infrastructure to solve their key challenges.
- Creating and maintaining reusable company‑wide libraries and infrastructure‑as‑code.
- Researching and integrating the best open‑source technologies to enhance Faculty’s infrastructure capabilities.
Who we’re looking for:
- You are pragmatic and outcome‑focused, balancing the big picture with the details to execute complex projects in the real world.
- You think scientifically, always testing assumptions, seeking evidence and looking for opportunities to improve how things are done.
- You have a drive to learn constantly, exploring new technologies and novel applications for existing tools.
- You possess deep experience with at least one major cloud provider (AWS, Azure or GCP) and Infrastructure as Code, especially Terraform.
- You are experienced in building and deploying containerized solutions using Docker and Kubernetes supported by strong CI / CD and GitOps practices.
- You possess proficient knowledge of networking and cloud security.
- You excel at working directly with clients and stakeholders, confidently handling requirements gathering, technical planning and scoping.
Recruitment Ethos:
We aim to grow the best team – not the most similar one. We know that diversity of individuals fosters diversity of thought and strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Benefits:
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working: We work from our Old Street office in London 2 days a week.
If you don’t feel you meet all the requirements but are excited by the role and know you bring some key strengths please do apply or reach out to our Talent Acquisition team for a confidential chat – Please know we are open to conversations about part‑time roles or condensed hours.
Cloud Engineer employer: Faculty AI
Contact Detail:
Faculty AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Cloud Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Faculty or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your cloud projects. This is your chance to demonstrate your expertise in AWS, Azure, or GCP, and it’ll make you stand out during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding and problem-solving skills. Practice common cloud engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from candidates who are genuinely excited about joining our team.
We think you need these skills to ace Cloud Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Cloud Engineer role. Highlight your experience with cloud providers like AWS, Azure, or GCP, and showcase any relevant projects that demonstrate your skills in building scalable infrastructure.
Showcase Your Technical Skills: Don’t hold back on your technical expertise! Mention your experience with Infrastructure as Code, especially Terraform, and your familiarity with containerisation tools like Docker and Kubernetes. This is your chance to shine!
Be Authentic: We love seeing your personality come through in your application. Share your passion for AI and technology, and don’t hesitate to express your curiosity and eagerness to learn. We’re looking for individuals who are excited about making a positive impact!
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 to join our team at Faculty!
How to prepare for a job interview at Faculty AI
✨Know Your Cloud Stuff
Make sure you brush up on your knowledge of major cloud providers like AWS, Azure, or GCP. Be ready to discuss your experience with Infrastructure as Code, especially Terraform, and how you've used it in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex challenges you've tackled in previous roles. Highlight how you approached these problems scientifically, tested assumptions, and implemented effective solutions that made a real impact.
✨Communicate Like a Pro
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Think about how you can convey your ideas clearly and confidently during the interview.
✨Demonstrate Your Curiosity
Faculty values intellectual curiosity, so come prepared to discuss new technologies you've explored or innovative applications you've considered. Show them you're always learning and eager to bring fresh ideas to the table.