At a Glance
- Tasks: Design and build scalable backend systems for enterprise GenAI products.
- Company: Join Scale AI, a leader in the enterprise AI revolution.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Be at the forefront of AI innovation and make a real impact.
- Qualifications: 4+ years in backend development with strong skills in Python or TypeScript.
The predicted salary is between 72000 - 88000 £ per year.
At Scale AI, we’re not just building AI tools—we’re pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting‑edge solutions that transform workflows, automate complex processes, and drive unparalleled efficiency for the largest enterprises. Our Scale Generative AI Platform (SGP) provides foundational services and APIs, enabling businesses to seamlessly integrate AI into their operations at production scale.
We’re looking for a Backend Engineer to help bring large‑scale GenAI systems to production. In this role, you’ll build the core infrastructure that powers AI products for some of the world’s largest enterprises—designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production‑grade reliability and performance. This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale.
If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you. At Scale, we don’t just follow AI advancements — we lead them. Backed by deep expertise in data, infrastructure, and model deployment, we are uniquely positioned to solve the hardest problems in AI adoption. Join us in shaping the future of enterprise AI, where your work will directly impact how businesses operate, innovate, and grow in the age of GenAI.
You Will:
- Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure.
- Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production‑scale AI adoption.
- Architect scalable distributed systems for data processing, inference, and orchestration of large‑scale GenAI workloads.
- Optimize backend performance for latency, throughput, and cost—ensuring AI applications can operate at enterprise scale across hybrid and multi‑cloud environments.
- Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large‑scale AI deployments.
- Collaborate with ML and product teams to bring cutting‑edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks.
- Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise‑ready.
Ideally, You Have:
- 4+ years of experience developing large‑scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript, with experience designing high‑performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.
- Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure‑as‑Code tools like Terraform.
- Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data‑intensive applications.
- Hands‑on experience with GenAI applications, model integration, or AI agent systems—understanding how to deploy, evaluate, and scale AI workloads in production.
- Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi‑tenant environments.
- Ability to balance rapid iteration with production‑grade quality, shipping reliable backend systems in fast‑paced environments.
- Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale.
About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com.
Software Engineer, Enterprise employer: Scale
At Scale, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London office provides unique opportunities for professional growth, with access to cutting-edge technology and the chance to work on impactful AI projects in the public sector. We value our employees' contributions and support their development through continuous learning and mentorship, making Scale a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer, Enterprise
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Scale or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Scale.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Scale.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Scale that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Software Engineer, Enterprise
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Scale.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Scale and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Scale
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Scale uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.