Associate Systems Engineer
Posted Updated
Description
Associate Systems Engineers support the integration design, testing and ongoing development of the integrations platform that connects Scoular's business applications, trading partners and data platforms. Working as part of an Agile Integration Team alongside senior integration engineers that build and maintain integrations using Azure Integration Services (Logic Apps, Service Bus, API Management, Event Grid, Azure Functions, Azure Storage and Azure SQL), help monitor the existing integrations environment, and assist with triaging and correcting exceptions within short timelines. Scoular builds software through an AI-assisted SDLC, so this role develops fluency with Claude Code from the start — working within the defined session lifecycle (kick-off, develop, code-review, build-check, wrap-up), on Scoular's .NET/C# and Azure stack, with all code in GitHub Enterprise. Because AI removes much of the effort of producing code, the skills that matter most early are the ones that make integrations trustworthy: source control, testing, understanding message formats and data mappings, reading and debugging code you did not write by hand, and knowing when to escalate. This entry-level role provides hands-on experience with enterprise integration, APIs, and automation while building a strong technical foundation for growth into an Integration Engineer role.
- Integration Development and Delivery: Develop, test and document integrations using Azure Integration Services (Logic Apps, Service Bus, API Management, Event Grid, Azure Functions, Data Factory, Azure Storage and Azure SQL) with Claude Code inside the defined session lifecycle, and .NET/C# for custom components. Submit work through pull requests for required review, use only approved packages, build from the established scaffolding baseline rather than starting fresh, and resolve security scan findings before promotion. Read, test and understand AI-generated code before submitting it — do not promote output you cannot explain. 30
- Integration Support and Monitoring: Help monitor the existing integrations environment and applications, triage failed messages and exceptions within short timelines and troubleshoot production issues with guidance from senior engineers. Escalate promptly, follow issues through to root cause resolution, and participate in L2/L3 support post-delivery.
- Partnership: Collaborate efficiently and effectively with integration engineers, IT teams, business stakeholders, third-party vendors and trading partners to understand integration requirements, and maintain an open line of communication on progress, risks and issues.
- Analysis and Design: Work with stakeholders and senior engineers to analyze integration requirements, document data mapping and message flows (JSON, XML, flat file and EDI), and contribute to functional and technical designs. Help keep business context current inside the repository so AI tooling and future maintainers inherit it.
- Change Management: Follow defined change management processes — documenting changes, supporting scheduling and communication, and assisting with implementation and post-change validation through the DEV / QA / PROD path with CI/CD pipeline-based deployment. Ensure all work is tested and reviewed before release to production.
- Learning and Technical Foundations: Build core integration proficiency deliberately — Git and GitHub fundamentals, Scoular's development standards, integration patterns and protocols (REST, SOAP, OAuth, OData), message transformation (XSLT, XPath, XSD), testing practice, and effective AI use including context management and prompt quality. Participate in enablement, paired mentoring and peer reviews with senior integration engineers, use the Skills Catalog and shared prompt library, and share learning openly including mistakes.
- Enterprise Architecture and Responsible AI: Support solutions that align with Scoular's technical architecture, integration strategy, Integration Team standards and SOPs to minimize environment complexity, support costs and technical debt — including read-only ODS consumption with write-backs through APIM only. Follow AI-specific Acceptable Use and ISO controls, and never place sensitive or unmasked production data into non-production environments. Escalate rather than improvise when a situation is not covered by a documented standard.