Software Engineer - Commercial Engineering & AI (CEAI)

## About the role - Adopt AI‑native development practices, leveraging AI tools across the SDLC while taking ownership of reviewing, validating, and improving AI‑generated outputs. - Develop and ship code for product features, applying standard coding practices, maintainability, and basic debugging, testing, and telemetry techniques. - Contribute to design and implementation by exploring solution options, supporting design documentation, and validating technical approaches under supervision. - Follow engineering excellence standards, including security, privacy, compliance, and accessibility practices, while building awareness of regulatory and system requirements. - Participate in testing and quality assurance, executing test plans, supporting automation, and ensuring reliability and regression prevention. - Support deployment and release processes, including safe change practices, feature rollout (flighting), rollback planning, and alignment with compliance requirements. - Assist in live-site operations and reliability, acting as DRI for live-site issues, monitoring systems, responding to incidents, and improving troubleshooting and telemetry. - Collaborate with stakeholders and learn continuously, contributing to understanding customer requirements, integrating feedback, reusing existing solutions, and improving documentation and team practices. ## Requirements - Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. - Experience with cloud technologies (Azure, AWS, Google). - Experience with distributed systems, micro-service architecture, scalability patterns, and high-availability architectures. - Experience with REST Based API's development, messaging patterns (e.g. Service bus, Event Hub, Storage Queues) and cloud storage technologies ( e.g. Cosmos DB). - Proficient in problem-solving skills, with a data-driven approach to debugging and performance optimization. - Experience in deploying, monitoring, and operating services in the cloud. - Problem-solving, troubleshooting, and organizational skills. - Experience with or exposure to Agile and iterative development processes. - Familiarity with modern engineering practices such as CI/CD and version control systems like Git.