API Architect with.NET
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.