Solutions Architect

Overview LSAC’s mission is to advance law and justice by promoting access, equity, and fairness in law school admission and supporting the learning journey from prelaw through practice. Pay rate: $160,000 to $173,000, depending on experience The Solutions Architect is responsible for designing and delivering scalable, secure, and high-performing technology solutions that align with LSAC business and mission objectives. This role bridges business needs and technical execution by translating requirements into architectural designs, ensuring systems are resilient, efficient, and future-ready. You will partner with product management, engineering teams, and the Director of Software Architecture to translate business goals into shipped software, with a particular focus on closing three gaps in our current operating model: increasing DevOps capacity, establishing infrastructure-as-code (IaC) as a first-class practice, and uplifting the patterns we use to support production systems. This is a senior individual contributor role: you will spend most of your time writing code – application code, IaC, deployment pipelines, and observability instrumentation – and the remainder shaping architecture, mentoring engineers, and partnering with peers across Cloud Architecture, SRE, and Product. Responsibilities Essential Job Functions Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of this position. The individual employed in this position will be required to: Lead the design and hands-on implementation of Azure-based solutions, with a core focus on reusability, scalability, fault-tolerance, and security. Author production code (.NET Core, React, services, APIs) – not just diagrams. Define and enforce patterns by building reference implementations rather than describing them. Establish infrastructure-as-code (IaC) as a foundational: build the initial modules, set the standards (e.g., Bicep or Terraform), and partner with teams to migrate existing infrastructure into version-controlled, peer-reviewed deployments. Design and build CI/CD pipelines and developer tooling that allows development teams to ship safely and frequently with minimal manual intervention. Stand up the production-support at scale: observability and SLOs, alerting, runbooks, on-call rotations, incident response practices, and post-incident reviews. Partner with the SRE team and support engineering to operationalize these patterns and uplift the current model where gaps exist. Lead the response to high-severity production issues; debug across the stack – front-end, services, data stores, and infrastructure – and ship the fix or mitigation. Design and implement microservices and APIs with thoughtfully defined contracts; build reusable components and libraries that other teams adopt. Provide technical leadership and code review across multiple agile teams (back-end, front-end, full-stack); raise the bar for quality, testability, and operational readiness. Collaborate with Cloud Architecture on Azure landing zones, networking, and identity to ensure platform-level decisions translate cleanly into application-level ones. Partner with product management to translate roadmap objectives into pragmatic technical plans, including MVP framing, sequencing, and trade-offs. Evaluate third-party tools and platforms; produce written recommendations grounded in technical assessment, cost, and operational impact. Communicate architectural decisions, trade-offs, and risks clearly in writing (architectural decision records, design docs, short proposals) and verbally to stakeholders ranging from engineers to senior leaders. Continuously look for and implement improvements in software delivery, platform reliability, and developer experience. Champion practical Gen-AI adoption: coach and mentor engineers on AI-assisted development (e.g., GitHub Copilot and Copilot Chat), prompt design, AI-augmented code review, and AI-accelerated test generation. Establish team-wide prompting standards and review practices for AI-generated code, and lead by example by using these tools in your own day-to-day work. Architect Generative AI capabilities as needed, including LLM integrations, retrieval-augmented generation (RAG), and agentic patterns; embed Responsible AI practices (content safety, PII handling, evaluation, audit logging) into the architecture from day one. Competencies Strong written and verbal communication skills. Holds a strong sense of accountability for both individual and team objectives. Embraces a forward-thinking mindset, contributing to a culture of continuous improvement and creativity. Excellent time management, prioritization, attention to detail and organization skills Bias for shipping: prefers writing code, IaC, and runbooks over slides and meetings, and demonstrates impact through working software in production. Deep, hands-on experience with Azure services (e.g., App Service, AKS or Container Apps, API