Solutions Architect

Role Description

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
• 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

• Lead the design and hands-on implementation of Azure-based solutions, focusing on reusability, scalability, fault-tolerance, and security.
• Author production code (.NET Core, React, services, APIs) – not just diagrams.
• Establish infrastructure-as-code (IaC) as a foundational practice.
• Design and build CI/CD pipelines and developer tooling for safe and frequent shipping.
• Stand up production support at scale: observability, SLOs, alerting, runbooks, on-call rotations, incident response practices, and post-incident reviews.
• Lead the response to high-severity production issues; debug across the stack.
• Design and implement microservices and APIs with thoughtfully defined contracts.
• Provide technical leadership and code review across multiple agile teams.
• Collaborate with Cloud Architecture on Azure landing zones, networking, and identity.
• Partner with product management to translate roadmap objectives into technical plans.
• Evaluate third-party tools and platforms; produce written recommendations.
• Communicate architectural decisions, trade-offs, and risks clearly to stakeholders.
• Continuously look for and implement improvements in software delivery and platform reliability.
• Champion practical Gen-AI adoption and mentor engineers on AI-assisted development.
• Architect Generative AI capabilities as needed, embedding Responsible AI practices.

Qualifications

• 10+ years of progressive experience designing and building large-scale, cloud-native platforms.
• Demonstrable track record of hands-on engineering supported by code samples or prior production systems.
• Production experience with Azure, .NET Core, and React (or comparable modern web stack).
• Experience leading the introduction or maturation of infrastructure-as-code and CI/CD practices.
• Experience standing up or significantly maturing site reliability engineering or production-support practices.
• B.A. or B.S. in Computer Science, Engineering, or a related field, or equivalent experience (preferred).
• Azure certifications such as Azure Solutions Architect Expert or DevOps Engineer Expert (preferred).
• Experience in EdTech, higher education, or other regulated or compliance-sensitive domains (preferred).
• Coursework, certifications, or verifiable project experience in applied AI/ML (preferred).

Requirements

• 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.
• Excellent time management, prioritization, attention to detail, and organization skills.
• Deep, hands-on experience with Azure services.
• Strong .NET Core and modern web (React) skills.
• Proven experience defining and operating IaC as code.
• Strong fluency with CI/CD systems and automated testing.
• Strong understanding of microservices, decoupled systems, and API design.
• Practical site reliability engineering experience.
• Comfortable working in agile environments.
• Calm under production pressure; able to make crisp, well-communicated decisions during incidents.
• Demonstrated production use of AI-assisted development tooling.
• Working knowledge of Generative AI architectures.
• Familiarity with Responsible AI principles.

Benefits

• Pay rate: $160,000 to $173,000, depending on experience.
• Remote and professional office environment.
• Up to 5% of travel required for occasional team off-sites or in-person collaboration.