Senior Fullstack Engineer: AI Frontend on Azure Hybrid

GCS Recruitment; Greater London; Hybrid; GBP 72,000 - 94,000; Full time

Benefits offered by this job

Hybrid working

Job summary

GCS Recruitment seeks two Senior Fullstack Engineers for an energy-sector project delivering AI-enabled capabilities on Azure. Lead the design of scalable front-end architectures and collaborate with backend, cloud, and AI teams to ship production-ready applications.

Role emphasizes building high-performance web apps, data-intensive processing, and seamless integration with AI APIs, with Docker and CI/CD involved. Hybrid London-based work pattern expected.

Qualifications

• Design, build and maintain scalable front-end applications using React and Python.
• Experience deploying front-ends to cloud platforms, ideally Azure (AWS acceptable).
• Familiar with APIs, microservices and distributed systems.
• Strong front-end performance and observability focus.

Responsibilities

• Design, build, and maintain scalable front-end applications using React, Python, and modern JavaScript/TypeScript.
• Build front-end solutions for high data throughput and performance at scale.
• Collaborate on deploying applications to Azure-based cloud environments.
• Integrate front-end applications with AI-powered services and Agentic AI systems.
• Work with Docker-based containerised environments and CI/CD pipelines.
• Support reliable, repeatable deployments and cloud-native orchestration.

Skills

React

Python

JavaScript/TypeScript

Performance optimisation

CI/CD

Tools

Docker

Azure

Microservices

APIs

Job description

GCS Recruitment seeks two Senior Fullstack Engineers for an energy-sector project delivering AI-enabled capabilities on Azure. Lead the design of scalable front-end architectures and collaborate with backend, cloud, and AI teams to ship production-ready applications.

Role emphasizes building high-performance web apps, data-intensive processing, and seamless integration with AI APIs, with Docker and CI/CD involved. Hybrid London-based work pattern expected.