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- Tasks: Design and develop scalable AI solutions using Python for financial markets.
- Company: Leading financial markets infrastructure provider with a focus on innovation.
- Benefits: Competitive salary, continuous professional development, and a diverse work environment.
- Why this job: Join high-impact projects and collaborate with data science teams to shape the future.
- Qualifications: Strong Python skills and knowledge of cloud technologies required.
- Other info: Dynamic workplace with opportunities for growth and learning.
The predicted salary is between 36000 - 60000 £ per year.
A financial markets infrastructure provider is seeking a Software Engineer - Python to develop scalable AI solutions. This role involves designing software, ensuring coding standards, and collaborating with data science teams.
Candidates should have strong Python experience and knowledge of cloud technologies. The position offers high-impact projects and opportunities for continuous professional development in a diverse work environment.
Python AI Backend Engineer in Edinburgh employer: London Stock Exchange Group
Contact Detail:
London Stock Exchange Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python AI Backend Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the financial tech space on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those related to AI and cloud technologies. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on coding challenges and system design questions. We recommend using platforms like LeetCode or HackerRank to practice and get comfortable with the types of problems you might face.
✨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 Python AI Backend Engineer in Edinburgh
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your strong Python experience in your application. We want to see how you've used Python in past projects, especially if it relates to AI or cloud technologies.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Software Engineer - Python role. We love seeing candidates who understand what we’re looking for.
Collaborate Like a Pro: Since this role involves working with data science teams, mention any collaborative projects you’ve been part of. We appreciate candidates who can work well in a team and contribute to high-impact projects.
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 us!
How to prepare for a job interview at London Stock Exchange Group
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python, including any frameworks or libraries you've used. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Familiarise Yourself with AI Concepts
Since the role involves developing AI solutions, it’s crucial to understand key AI concepts and how they apply to backend development. Be prepared to talk about any relevant projects you've worked on and how you approached AI integration in those projects.
✨Cloud Technologies are Key
The job description mentions cloud technologies, so make sure you know your way around them. Whether it's AWS, Azure, or Google Cloud, be ready to discuss your experience and how you've leveraged these platforms in your previous work.
✨Collaboration is Crucial
This role requires working closely with data science teams, so highlight your teamwork skills. Think of examples where you've successfully collaborated on projects, and be ready to explain how you communicate technical concepts to non-technical team members.
