API Architect

Job Description

API Architect with .NET

Location: Hybrid- London, UK

Inside IR35- Long term Contract.

Role Overview We are looking for a highly skilled :

.NET API Technology Architect to drive the technical design, structure, and implementation of our enterprise API ecosystem.

In this role, you will focus on translating business requirements into robust, high-performance technical frameworks,with a foundational emphasis on building world-class Restful services.

You will be the go-to technical expert for the .NET ecosystem, containerization(Docker/Kubernetes), and clean code practices.

Additionally, we are looking for a modern architect who actively utilizes AI-driven engineering tools to optimize workflows, accelerate design phases, and maintain a competitive edge.

Key Responsibilities

API Technology & REST Standards Design.

• Define, design, and enforce strict REST API standards and governance across all enterprise services, ensuring high-throughput, security, and resilience.
• Implement advanced architectural patterns such as Microservices, Domain-Driven-Design (DDD), CQRS, and Event-Driven Architecture.
• Design uniform resource naming, versioning strategies, payload structures, and robust error-handling mechanisms standard to enterprise RESTful environments.
• Define data modeling, caching strategies, and integration patterns across microservices. Containerization & Platform Orchestration
• Architect container-native development and deployment workflows using Docker.
• Design, configure, and optimize enterprise deployments on Kubernetes (K8s),managing ingress, service meshes, scalability, and resource limits. Code Quality & Engineering Standards
• Establish rigorous code quality baselines, promoting SOLID principles, classic design patterns, and clean architecture templates.
• Set standards for testing automation (unit, component, and integration testing) and ensure secure coding practices are embedded in the API lifecycle.
• Conduct deep-dive technical reviews to resolve complex architectural bottlenecks and technical debt. AI-Assisted Engineering
• Integrate AI productivity tools (e.g., GitHub Copilot, advanced LLM prompt engineering, AI code review tools) into the architectural and development lifecycle to increase velocity.
• Guide engineering teams on best practices for safely and effectively leveraging AI tools during development and refactoring.