Senior Back End Engineer

W Talent
London, United Kingdom
Today
£80,000 – £120,000 pa

Salary

£80,000 – £120,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Senior
Education
Degree
Posted
1 May 2026 (Today)

Senior Backend Engineer

Location: London

Work Type: On-site

Company Description

We are a rapidly growing consumer technology company operating at the intersection of AI, aesthetics, and digital experiences. With a global community of millions, we are building innovative AI-driven products that are transforming how users engage with and understand visual data.

Our offerings range from consumer-facing AI analysis tools to partnerships with leading global brands. As we scale quickly, we are expanding our team and pushing the boundaries of how technology and user experience come together.

Role Description

We are seeking a talented Senior Backend Engineer to join our London-based team full-time. You will play a key role in building and scaling the core infrastructure of our AI platform, owning critical backend systems, and supporting rapid product growth.

This is a high-impact, fast-paced role with significant autonomy, where your work will directly influence product direction and user experience.

Key Responsibilities

Design and implement backend services and APIs using Python, FastAPI, and Django

Build and maintain scalable RESTful APIs with PostgreSQL

Develop and integrate AI/LLM-powered features using frameworks such as LangChain

Implement and manage payment systems, including Stripe integrations and subscription flows

Build image processing and computer vision pipelines

Write clean, maintainable, and well-documented code deployed via Docker and CI/CD pipelines

Collaborate using GitHub, maintaining high code quality and team standards

Work with BaaS platforms (e.g., Supabase) for authentication, storage, and real-time functionality

Ensure performance, scalability, and security best practices

Collaborate cross-functionally with Product, Design, and Frontend teams

Contribute to architectural decisions and mentor other engineers

Develop data-driven backend services and pipelines

Support production systems and deployments within a small, high-performing team

Qualifications

5+ years of professional software engineering experience

Strong Python expertise with backend development experience

Proven experience with FastAPI and/or Django, REST APIs, and PostgreSQL

Experience integrating Stripe for payments and subscriptions

Familiarity with image processing and computer vision

Experience with Docker, GitHub, and modern deployment workflows

Knowledge of cloud platforms (AWS, GCP, or Azure)

Strong understanding of software design principles (SOLID, patterns, clean code)

Experience with BaaS platforms such as Supabase or Firebase

Ability to thrive in fast-paced, high-ownership environments

Nice to Have

Experience with LLM APIs (e.g., OpenAI, Anthropic, Gemini) and LangChain

Background in AI/ML (e.g., generative models, GANs, diffusion, regression)

Experience building data pipelines and data-driven systems

Familiarity with workflow orchestration tools (e.g., Temporal, Prefect)

Why Join

Be part of a fast-growing company in the AI and consumer tech space

High ownership and autonomy over technical decisions

Work closely with founders and a mission-driven team

Strong market traction and growth potential

Opportunity to shape a rapidly evolving industry

Related Jobs

View all jobs

Senior/Staff Software Engineer, Back End Leaning

Synthesia London, United Kingdom
£70,000 – £120,000 pa Remote

Software Engineer, Back End Leaning (Tech Lead Level)

Synthesia London, United Kingdom
Remote

Software Engineer, Machine Learning

Synthesia London, United Kingdom
Remote

Software Engineer (Principal level)

Synthesia London, United Kingdom
Hybrid

Forward Deployed Applications - Senior Software Engineer

PhysicsX London, United Kingdom

Senior Simulation Data Engineer

PhysicsX London, United Kingdom

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.