Senior Backend Engineer: AI-Native FinTech on Azure, Remote

M-KOPA; Manchester; Remote; GBP 65,000 - 95,000; Full time

Benefits offered by this job

Personalised training budget

Home office setup budget

Professional development programs and

Flexible working arrangements

Well-being support

Job summary

M-KOPA is seeking a senior backend engineer to join our Asset Sales group, building distributed C#/.NET microservices on Azure within an AI-native engineering approach. You will own services end-to-end—from idea to production—while working in a fully remote, GMT-aligned environment across UK, Europe, and Africa.

You’ll collaborate across time zones, leverage observability tools like Grafana and Application Insights, and contribute to scale, reliability, and experimentation with AI tooling.

Qualifications

• Strong grasp of C# and .NET development.
• Experience with event-driven systems (Azure Service Bus, Kafka, RabbitMQ).
• Microservices on Azure and Kubernetes.
• Observability tooling (Grafana / App Insights) to understand production behavior.
• Comfort with AI tools as part of daily engineering workflow.

Responsibilities

• Build and operate distributed C#/.NET microservices on Azure.
• Own end-to-end delivery from idea through deployment to production.
• Work in an AI-native engineering environment and contribute to scalable architecture.
• Collaborate across time zones in a distributed team environment.

Skills

C#

.NET

Azure

Event-driven

Microservices

Kubernetes

Observability

AI tools

DevOps culture

Distributed teams

Tools

Azure

Kubernetes

Grafana

Application Insights

Claude

Job description

M-KOPA is seeking a senior backend engineer to join our Asset Sales group, building distributed C#/.NET microservices on Azure within an AI-native engineering approach. You will own services end-to-end—from idea to production—while working in a fully remote, GMT-aligned environment across UK, Europe, and Africa.

You’ll collaborate across time zones, leverage observability tools like Grafana and Application Insights, and contribute to scale, reliability, and experimentation with AI tooling.