Full Stack Engineer

Job Title: Senior / Principal Full Stack Engineer (TypeScript / React + GenAI)

Location: Basingstoke, UK (Hybrid – 2 days onsite per week)

Rate: £550 per day (Outside IR35)

Duration: Initial 6 months (with likely extension)

Overview:

We are supporting a global enterprise as they expand their platform engineering capability, with a particular focus on embedding Generative AI into core business systems.

This role is positioned as a full stack engineering role first, with AI/GenAI forming a key component of the wider technology stack. The successful candidate will play a critical role in building and scaling production-grade applications, whilst integrating AI capabilities into real-world, enterprise use cases.

Key Responsibilities:

• Design, build and maintain full stack applications, with a focus on scalable, backend-led architecture
• Develop modern web applications using TypeScript and React
• Integrate Generative AI capabilities into enterprise platforms and workflows
• Build and consume APIs, working across data pipelines and cloud-based services
• Contribute to CI/CD pipelines, automation, and engineering best practices
• Collaborate closely with product, engineering and data teams to deliver high-quality solutions
• Support the adoption and integration of AI capabilities across the wider business

Key Requirements:

• Strong commercial experience as a Full Stack Engineer, with a focus on TypeScript and React
• Proven track record building production-grade systems in enterprise environments
• Hands-on experience working on commercial AI / GenAI projects (e.g. LLM integrations, embeddings, AI-enabled features)
• Experience working with APIs, microservices and modern application architectures
• Solid understanding of cloud platforms (e.g. Azure, GCP) and DevOps practices (CI/CD, containerisation)
• Ability to operate effectively within complex, cross-functional teams

Desirable Experience:

• Exposure to Python within backend or AI-related services
• Experience integrating AI capabilities into customer-facing or internal platforms
• Familiarity with MLOps principles or deploying AI solutions into production environments
• Background working in regulated or large-scale enterprise environments