[Remote] Lead Software Engineer
Note: The job is a remote job and is open to candidates in USA. Rule42 is a sports technology company modernizing amateur athlete discovery through an AI-powered platform. The Lead Software Engineer will build and operate distributed systems supporting AI platforms, data products, and customer-facing applications, with responsibilities spanning scalable architecture, cloud infrastructure, production reliability, and technical leadership.
Responsibilities
- Design, develop, and maintain distributed systems using event-driven architecture patterns
- Build scalable .NET Core microservices, APIs, and platform services that support AI and data-driven products
- Own the reliability, performance, and operational health of production systems
- Design and implement resilient architectures with appropriate fault tolerance, observability, and recovery mechanisms
- Develop and maintain cloud-native solutions within Google Cloud Platform (GCP)
- Work with our IT Director to implement scalable storage solutions our system will use
- Collaborate with data engineers, machine learning engineers, product leaders, and business stakeholders to deliver platform capabilities
- Establish engineering best practices for code quality, testing, deployment automation, monitoring, and incident response
- Lead troubleshooting and root-cause analysis of production issues
- Maintain and continuously improve CI/CD pipelines and software delivery processes
- Participate in architectural planning and technical decision-making for the company's long-term platform strategy
Skills
- Bachelor's degree in Computer Science, Information Systems, or a related technical discipline
- 7+ years of professional software engineering experience
- 3+ years acting in a lead capacity
- Strong experience developing applications and services in C# (.Net Core) and Python
- Strong experience designing and optimizing SQL-based data systems (Postgresql)
- Strong understanding of software design patterns, system scalability, reliability, and performance optimization
- Experience building and operating solutions on Google Cloud Platform (GCP)
- Experience developing distributed systems and event-driven architectures
- Experience building RESTful APIs and microservices
- Experience supporting and maintaining production environments
- Experience with modern CI/CD practices and automated deployment pipelines
- Master's degree in Computer Science, Software Engineering, or a related technical discipline
- Experience supporting machine learning platforms, data products, or AI-driven applications
- Experience with containerized environments and orchestration technologies
- Experience implementing observability solutions, including monitoring, logging, and distributed tracing
- Experience designing highly available and fault-tolerant cloud architectures
- Experience building data platforms and working with video analytics
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