• The position requires a skilled and self-driven Software Engineer with deep technical expertise in Go-based systems and practical experience building modern web and distributed applications. • Strong engineering capabilities with the ability to navigate the complexities of third-party integrations. • Consistently applies security best practices as a matter of course. • Embraces AI tooling responsibly — maintaining full accountability for every line of code they ship.

• Design, build, and operate backend services for generative AI capabilities, including LLM-backed APIs, agents, retrieval and knowledge layers, and connectors to internal and external systems. • Build and scale data infrastructure underpinning file management and high-throughput data flows between customer environments, cloud object storage, and compute clusters, with an emphasis on reliability, performance, and cost. • Work across the stack—from backend services (Python/Java/Go) and cloud infrastructure (AWS/Azure/GCP, containers/Kubernetes) to the occasional UI change—to deliver end-to-end user-facing experiences in collaboration with product, design, and other engineering teams.

• Build, maintain, and improve backend services, APIs, and data pipelines that power integrations with external partners and internal systems. • Design and implement scalable, reliable integration patterns for third-party APIs and data exchange. • Ensure the performance, reliability, and accuracy of data flowing across systems. • Debug and troubleshoot issues across distributed systems, integrations, and data pipelines. • Partner with product, operations, and engineering to translate integration requirements into technical solutions. • Participate in system design discussions, code reviews, and team knowledge sharing. • Contribute to improving developer experience through better tooling, documentation, and integration workflows. • Support monitoring, logging, and alerting to proactively identify and resolve issues.

• Build, maintain, and improve backend services, APIs, and data models that power clinician workflows and reporting. • Collaborate with front-end engineers to integrate backend functionality into dashboards, reporting tools, and other clinical applications. • Ensure the reliability, scalability, and performance of data-driven systems. • Participate in system architecture discussions, code reviews, and knowledge sharing. • Debug and troubleshoot issues across backend services and pipelines. • Partner with product and design to translate clinical requirements into technical solutions. • Stay up to date with modern software engineering practices across both frontend and backend development.