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- Tasks: Lead backend development for scalable cloud infrastructure and innovative agentic frameworks.
- Company: Join a pioneering tech firm focused on autonomous systems and cutting-edge technologies.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be at the forefront of technology, shaping the future with your engineering skills.
- Qualifications: Strong understanding of distributed systems and a degree in Mathematics or Physics preferred.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
We are building a massively scalable cloud infrastructure designed for data integration and complex digital twins, utilizing cutting-edge graph theory and physics-based modeling. We are looking for an engineer to lead the development of our backend services and Agentic Framework. We don’t just "plug tools into an LLM"; we are architecting autonomous systems. While our current stack is Python-based, we value engineers who understand architectural concepts (Async I/O, Distributed Systems, Graph Theory) over specific syntax. If you are a skilled engineer from a different language background (Go, Rust, C++) with the right mindset, we want to hear from you.
Note: Due to the complexity of the domain, there is a strong preference for candidates with a degree in Mathematics or Physics.
Key Responsibilities- Agentic Architecture: Design and maintain our agentic framework (currently using LangGraph). You will move beyond simple prompt engineering to build orchestrators that manage state, context, and complex reasoning loops.
- Core Service Development: Maintain and expand high-performance REST APIs and calculation engines ensuring clean installation, testing, and modularity.
- Scalable Cloud Infrastructure: Manage a hybrid architecture of containerized services (e.g. ECS/Fargate) and serverless components (e.g. AWS Lambda), ensuring seamless deployments via IaC.
- Data & Geospatial Engineering: Optimize complex data flows involving PostgreSQL/PostGIS for vector tiles and geospatial features, alongside Redis for caching and session management.
- DevOps & Quality: Enforce rigorous CI/CD standards, automated testing (unit/integration), and observability (logging/metrics) to ensure production reliability.
- Strong background in distributed systems, graph theory, and async I/O.
- Experience with architectural concepts over specific syntax; Python-based stack but open to Go, Rust, C++.
- Degree in Mathematics or Physics preferred.
Back End Developer employer: Data Insights AI
Contact Detail:
Data Insights AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Back End Developer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We can’t stress enough how important it is to make connections; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Build a portfolio that highlights your projects, especially those involving distributed systems or graph theory. We love seeing practical applications of your knowledge, so make sure to showcase what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your architectural concepts. We want to see how you think, so practice explaining your thought process and problem-solving approach clearly and confidently.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate engineers who are ready to dive into our cutting-edge projects.
We think you need these skills to ace Back End Developer
Some tips for your application 🫡
Show Off Your Skills: When you're writing your application, make sure to highlight your experience with distributed systems and async I/O. We want to see how your background aligns with our needs, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific skills and experiences that match our job description. We love seeing candidates who take the extra step to connect their background with what we’re looking for.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points where necessary and avoid jargon unless it’s relevant to the role. Remember, clarity is key!
Apply Through Our Website: Make sure to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Data Insights AI
✨Know Your Architecture
Make sure you understand the architectural concepts mentioned in the job description, like Async I/O and Distributed Systems. Be ready to discuss how these concepts apply to your past projects, even if they were in a different programming language.
✨Showcase Your Problem-Solving Skills
Prepare to demonstrate your ability to tackle complex problems, especially those related to data integration and geospatial features. Think of examples where you've optimised data flows or built scalable systems, and be ready to explain your thought process.
✨Brush Up on Graph Theory
Since the role involves graph theory, it’s a good idea to review key concepts and be prepared to discuss how you’ve applied them in your work. If you have experience with similar frameworks, make sure to highlight that during the interview.
✨Emphasise Your DevOps Knowledge
Familiarise yourself with CI/CD practices and tools, as well as containerisation and serverless architectures. Be prepared to talk about how you’ve implemented these in previous roles to ensure production reliability.
