Senior Backend Engineer - AI Platform (f/m/d)

Contentful
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer - Research

Senior Data Scientist

Senior Data Engineer

Senior Data Engineer (AWS, Airflow, Python)

Senior Data Engineer (Microsoft Fabric)

About the Opportunity

Join Contentful as an AI Software Engineer (f/m/d) and innovate with AI Integrations

At Contentful, we empower thousands of customers to manage content at scale with speed, flexibility, and precision. We are seeking talented Senior AI Software Engineers (f/m/d) to join our AI Platform team—a group dedicated to building and maintaining an internal AI platform that accelerates innovation across our organization.

As a key contributor, you will help shape the internal AI ecosystem by developing scalable, high-performance AI integrations, APIs, tools and documentation that empower feature teams to efficiently test, deliver and maintain cutting-edge AI-driven products. Acting as both a support and consultancy resource, you’ll collaborate closely with feature teams to enhance their development capabilities and bring AI-powered solutions to life. By building intuitive internal tooling and fostering seamless integration of AI technologies, your work will drive efficiency and innovation throughout Contentful.

If you are passionate about advancing AI technology, enabling teams with powerful tools, and redefining how we build and deliver AI solutions, we’d love to have you join us. Together, we’ll build systems that set new standards for AI integration and empower our teams to create smarter, more impactful content solutions.

What to expect?

Collaborate and Innovate:Work closely with product managers, designers, and other engineers to build best-in-class AI-enabled features for our customers, ensuring seamless integration of AI technologies with existing systems.Platform Development:Design, develop, and maintain scalable AI platform features using TypeScript and Node.js, to enable feature teams, while ensuring they are compatible with other services, and APIs.AI Integration:Implement and integrate AI technologies, such as generative AI, machine learning models, or NLP, to enhance our platform’s capabilities, optimize processes, and improve user experiences.Holistic Thinking:Think critically about the interactions between AI models and product components to ensure a cohesive and intuitive user experience.Rapid Problem-Solving:Quickly fix bugs and solve problems, particularly related to AI performance, model integration, or data pipeline issues, to enhance customer satisfaction.Continuous Improvement:Participate in code reviews and contribute to improving our AI development processes, ensuring that the AI components are scalable, efficient, and maintainable.Stay Current:Keep up-to-date with the latest industry trends, particularly in the domains of AI and machine learning, ensuring the platform stays competitive by leveraging cutting-edge AI technologies.

What you need to be successful

API and Service Design: Proven experience in building APIs and services that efficiently handle large volumes of traffic. Deep interest in clean code practices and familiarity with enterprise architectural design patterns.Serverless Architectures: Experience with serverless architectures, ideally edge compute environments such as Cloudflare Workers.Asynchronous Systems: Experience with building and maintaining asynchronous systems for automation and bulk use cases.Containerization and Orchestration:Experience with Docker and Kubernetes, especially in deploying AI models or microservices.Enterprise Solutions:Knowledge with implementing enterprise ready governance features such as RBAC, audit logging, and compliance frameworks. Cloud Services Familiarity:Knowledge of cloud platforms like AWS, Azure, or GCP. Experience with services such as AWS SageMaker, Google AI, or Azure Machine Learning is a plus.Problem-Solving Skills:A natural problem-solver who brings forward innovative ideas to integrate and features within product workflows, leading to practical solutions and product growth.Collaborative Mindset:Excellent communication skills and the ability to collaborate effectively in a team environment.Adaptability:Ability to organize and prioritize competing workloads in a fast-paced, AI-driven environment, ensuring AI and software systems align with business objectives.

Preferred:

AI and Machine Learning Expertise:Skills in integrating and implementing AI/ML solutions within a product development environment. Skills in foundational models, prompt engineering and understanding to validate the quality of AI products.Platform Experience: Experience in developing platform features to enable internal teamsFull Stack Experience:Strong skills in TypeScript, React, and Node.js.

What's in it for You?

Join an ambitious tech company reshaping the way people build digital experiences Full-time employees receive Stock Options for the opportunity to share in the success of our company Comprehensive healthcare package covering 100% of monthly health premiums for employees and 85% of costs for your dependents. Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family. We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, compassion days for loss, education days, and volunteer days Company paid parental leave to care for and focus on your growing family Use your personal annual education budget to improve your skills and grow in your career Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties An annual wellbeing stipend to care for your physical, financial, or emotional health A monthly communication stipend and phone hardware upgrade reimbursement New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best

#LI-SB1 #LI-Hybrid

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.

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.