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- Tasks: Lead the design and architecture of AI capabilities for a scalable platform.
- Company: Global tech company transforming investment technology in Edinburgh.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join an innovative team and shape the future of AI technology.
- Qualifications: Strong programming skills in Python, Go, or Java; cloud experience required.
- Other info: Collaborative environment with a focus on best engineering practices.
The predicted salary is between 43200 - 72000 £ per year.
A global technology company is seeking a Staff Infrastructure Software Engineer for its AI Platform team in Edinburgh. The ideal candidate will lead the design and architecture of AI capabilities, focusing on building a scalable platform.
Key responsibilities include:
- Developing production run times for AI products
- Collaborating with cross-functional teams
- Adherence to best engineering practices
Strong programming skills in Python, Go, or Java as well as experience with cloud environments are essential. Join an innovative team transforming investment technology.
Staff AI Platform Infrastructure Engineer in Edinburgh employer: Addepar
Contact Detail:
Addepar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff AI Platform Infrastructure Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and infrastructure space on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Go, or Java. This will give potential employers a taste of what you can bring to their AI platform team.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding cloud environments. Practice common algorithms and system design questions to impress during the interview process.
✨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 seeing candidates who are proactive about their job search!
We think you need these skills to ace Staff AI Platform Infrastructure Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI platforms and cloud environments. We want to see how your skills in Python, Go, or Java can contribute to our team!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI technology and how you can help us build a scalable platform. Be genuine and let your personality shine through!
Showcase Your Projects: If you've worked on relevant projects, whether personal or professional, include them in your application. We love seeing real-world examples of your programming skills and engineering practices.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Addepar
✨Know Your Tech Inside Out
Make sure you brush up on your programming skills in Python, Go, or Java. Be ready to discuss your past projects and how you've used these languages to solve real-world problems, especially in cloud environments.
✨Showcase Your Architectural Skills
Prepare to talk about your experience with designing scalable platforms. Think of specific examples where you led the architecture of a project, and be ready to explain your thought process and the challenges you faced.
✨Collaboration is Key
Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated with others. Highlight your communication skills and how you ensure everyone is on the same page.
✨Emphasise Best Practices
Familiarise yourself with best engineering practices relevant to AI development. Be ready to discuss how you implement these practices in your work, and why they are important for building reliable and efficient AI products.
