Senior .NET Engineer $$$$ Offline

What You’ll Do 

● Design, develop, and maintain scalable APIs and backend services (.NET / .NET Core, AWS). 

● Build and manage data pipelines and integrations with AI systems and external platforms. 

● Work with modern infrastructure and data tools such as Docker, Kubernetes, Kafka, OpenSearch, and Redis. 

● Implement strong CI/CD, monitoring, and deployment practices for reliability and repeatability. 

● Collaborate closely with AI, QA, and product teams to translate business and research needs into technical solutions.

● Balance speed and scalability — deliver fast, but design for growth. 

● Contribute to architecture discussions and help evolve our backend stack for long-term success. What Success Looks Like (6–12 Months) 

● Production-grade, scalable backend components supporting real-time AI-driven features. 

● Clean, maintainable, and well-tested codebases deployed with strong observability. 

● Effective collaboration with AI and QA teams — fast iteration, shared ownership, and clear delivery rhythm. 

● Meaningful contribution to engineering culture — high accountability, continuous improvement, and curiosity.

What You Bring 

● 6+ years of experience in backend engineering in .NET / .NET Core and AWS environments. 

● Proven experience building APIs, distributed systems, and data pipelines in production. 

● Solid understanding of system design, scalability, reliability, and performance optimization. 

● Familiarity with modern cloud and data technologies (Docker, Kubernetes, Kafka, OpenSearch, Redis, etc.) — or the drive and curiosity to learn them quickly. 

● Excellent debugging and problem-solving skills — comfortable owning features end-to-end.

 ● Strong system design and architecture judgment; knows tradeoffs and can explain them clearly. 

● Strong product sense — understands tradeoffs, iteration speed, and value delivery. 

● Comfortable in dynamic startup environments: adaptable, pragmatic and flexible.

 ● Deep “vibe coding” experience — has built and debugged systems end-to-end using different AI tools and methods, and is forward-looking enough to recognise that AI-assisted engineering is the future