Company is a leading in the field of computer vision and AI for livestock farming. Operating in the global market, company develops advanced solutions for monitoring and optimizing pig growth and welfare. The company has strategic partnerships with major industry partners, including a leading biopharmaceutical company and a global technology solutions provider. We’re looking for a Senior Backend Engineer to help design, build, and scale the systems that power FarmSee’s AI-driven products. You’ll work closely with the AI and QA teams to build robust, cloud-based backend services and data pipelines — balancing high performance with reliability and scalability. This is a hands-on role in a fast-moving startup, where impact, curiosity, and technical depth matter more than job titles. 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. Requirements: 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 recognize that AI-assisted engineering is the future