About this role

What You'll Do
At M-KOPAs, you'll build and operate distributed C# and .NET microservices on Azure, working within an event-driven architecture at significant scale. This is an outcomes-driven role: we care far more about the value you create than where you sit or how many hours you're online. You'll own what you build end-to-end — from idea, through implementation and deployment, into production and iteration.

Technical Environment

Modern C# stack: Distributed C# and .NET microservices
Cloud & orchestration: Hosted on Azure using Kubernetes
Architecture: Event-driven, supporting products used at significant scale
Observability: Grafana, Azure Application Insights, logs, traces, and metrics
AI tooling: Claude and other AI tools used throughout the engineering workflow — design exploration, code generation and review, test writing, incident investigation, and technical communication

Our Engineering Approach

AI-native engineering: We want engineers who tinker — experimenting with new tools, agents, and workflows, and sharing what works
Guardrails as we accelerate: Automated tests, SLOs, alerting, observability, and deployment safeguards around everything we ship
Own it beyond the pull request: Design for idempotency, retries, out-of-order events, and failure modes, and know how your services behave in production
The Campfire Rule: Leave the systems you touch a little better than you found them
On-call as feedback, not heroics: Engineers who build our systems also help operate them, using incidents to make the platform more resilient

What You Need

We're looking for a senior engineer who's curious, autonomous, and highly trusted. You're comfortable owning the entire software stack — including supporting infrastructure — throughout its lifecycle, and you see production data, not just deployment, as the real measure of "done."

Required Experience:

Strong grasp of C# and .NET development
Experience with event-driven systems - We use Azure Service Bus, but would love to hear from you if you have experience with similar messaging technology (Kafka, RabbitMQ, etc.)
Microservices architecture experience, ideally on Azure and Kubernetes
Experience using observability tooling (e.g. Grafana, Application Insights) to understand production behaviour
Comfort using AI tools as part of a daily engineering workflow (design, code review, testing, incident investigation)
DevOps culture mindset, including on-call/production ownership
Proven ability to collaborate effectively in distributed teams across time zones
Continuous learning mindset and openness to feedback

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