Senior Backend Engineer in London

We are seeking a Senior Backend Engineer to join our Emerging Tech team and build the backend systems powering our multimodal AI platform. You will design and develop scalable APIs, services, and infrastructure that enable content discovery, semantic search, recommendation, and personalization capabilities across various media formats.

A SNAPSHOT OF YOUR RESPONSIBILITIES

• Own backend services from content curation, to semantic search and content recommendation from design to production deployment.
• Build and maintain microservices, cloud workflows and data pipelines that serve both internal editorial use-cases and consumer-facing applications.
• Integrate with model serving endpoints, vector search APIs, and LLM inference services to power AI-driven features.
• Build reliable, scalable cloud-native backend infra on multi-cloud platforms (GCP, AWS, Azure) with consideration for availability, performance, and cost.
• Mentor junior engineers, conduct code and design reviews, and take ownership of code quality, test coverage, and documentation.
• Collaborate with ML engineers, data engineers, and product leaders to craft end-to-end solutions.
• Ensure all systems adhere to security best practices for compliance with Fox policies on data protection and user privacy.
• Follow TDD/BDD approach with automated testing (unit, integration, end-to-end) practices to ensure quality.

WHAT YOU WILL NEED

• Proven track record of backend engineering experience working on production-grade systems in a product-focused organization.
• Strong programming skills in TypeScript and/or Python with solid computer science foundation in data structures and algorithms.
• Experience designing and building RESTful APIs and microservices at scale.
• Expertise in distributed systems design and architecture with focus on reliability and scaling.
• Experience with various types of data processing and persisting solutions (Apache Spark, PostgreSQL, MongoDB, Redis, Kafka).
• Cloud platform experience (GCP preferred: Cloud Run, Cloud Functions, Pub/Sub, Cloud Storage, Workflow, Firestore, AlloyDB, BigQuery).
• Experience integrating LLMs and other ML models serving endpoints.
• Understanding of multi-modal embeddings, vector search, and various similarity/semantic search patterns.
• Strong analytical and problem‐solving skills with ability to understand complex systems.
• Experience with CI/CD pipelines, containerization (Docker), and infrastructure‐as‐code.
• Ownership mindset with end‐to‐end responsibility for design, implementation, and production operation.
• Excellent grasp of SDLC and agility methodology, well versed with challenges in developing and releasing a globally distributed team.

NICE TO HAVE, BUT NOT A DEALBREAKER

• Experience with AI platforms and ML model serving infrastructure (e.g., Vertex AI, SageMaker, or similar).
• Experience with media processing pipelines and delivery systems (e.g. new articles, episodes, blogpost, video, podcasts).
• Familiarity with vector databases and semantic search systems (e.g. pgVector, Opensearch/Elasticsearch, Pinecone).
• Experience with Google Cloud Vertex AI and other AI service (e.g. OpenAI, Anthropic Claude, ElevenLabs).
• Curiosity and enthusiasm for generative AI, LLMs, and Agentic workflows.
• Open‐source contributions or active participation in the developer community.