Principal Software Architect Generative AI & Platform Engineering

• Define and lead the architectural strategy for generative AI across Risepoint’s platform, enabling scalable, high-quality solutions that expand access to affordable, workforce-relevant education.

• Design and evolve the AI platform layer, including model orchestration, prompt management, retrieval-augmented generation (RAG) patterns, evaluation pipelines, and responsible AI guardrails to ensure reliable and ethical outcomes.

• Establish experimentation frameworks that allow teams to test, compare, and optimize AI models, prompts, and retrieval strategies—driving continuous improvement in student and partner experiences.

• Develop and operationalize evaluation standards for AI output quality, including feedback loops and performance thresholds that ensure accuracy, consistency, and long-term model improvement.

• Drive build-vs-buy decisions for AI tools, platforms, and infrastructure, balancing speed, cost, scalability, and long-term maintainability.

• Partner cross-functionally with Product, Engineering, and Data teams to translate business needs into scalable technical solutions that support university partners and learner success.

• Lead architectural reviews and establish standards, patterns, and best practices that enable teams to build consistently and efficiently across the organization.

• Own and operate the Architecture Review Board (ARB), defining governance processes, decision criteria, and documentation practices (e.g., architecture decision records) to guide technical direction.

• Ensure AI and platform solutions are built on reliable, well-governed data by collaborating closely with data and analytics teams on data quality, access, and compliance.

• Identify and mitigate architectural risks early, proactively addressing scalability, performance, and reliability challenges before they impact delivery.

• Mentor and elevate senior engineers, fostering engineering excellence and strengthening architectural capability across the organization.

• Contribute to hiring and growing the architecture practice, helping build a high-performing team aligned to Risepoint’s mission and long-term technology strategy.

What Success Looks Like

• Establishes a clear, scalable architecture for generative AI that enables teams to efficiently build and deliver high-quality, reliable features across the platform.

• Drives measurable improvements in AI performance and consistency by implementing strong evaluation frameworks, experimentation practices, and feedback loops.

• Influences technical direction across teams, ensuring solutions are aligned, well-governed, and support Risepoint’s mission to expand access to high-quality, workforce-relevant education.

How Impact Will Be Measured

• Establish the AI architecture foundation: Define and implement core architectural patterns, standards, and governance (including the Architecture Review Board and ADRs) that enable multiple teams to consistently build and scale GenAI solutions.

• Operationalize AI quality and experimentation: Launch evaluation frameworks, experimentation capabilities, and feedback loops that drive measurable improvements in model performance, reliability, and responsible AI usage.

• Drive cross-functional adoption and impact: Partner with Product, Engineering, and Data teams to deliver production-ready AI use cases that demonstrate clear value for university partners and learners, while influencing technical direction across the organization.

Experience That Matters Most

• Deep technical and architectural expertise: 10+ years of software engineering experience, including time in a principal or staff architect role, with a proven track record of designing and scaling complex, cloud-native systems and setting technical direction across multiple teams.

• Hands-on experience with AI/ML and GenAI systems: Demonstrated experience building and deploying LLM-based applications in production, including familiarity with vector databases, embedding pipelines, RAG patterns, and model evaluation frameworks, along with a strong understanding of responsible AI and data governance.

• Cross-functional leadership and influence: Ability to translate business needs into technical solutions, influence without direct authority, and communicate effectively with both technical and non-technical stakeholders; experience mentoring engineers and contributing to building high-performing teams.

Experience That's Great To Have

• Experience in EdTech, higher education, or scaled SaaS environments, with an understanding of building multi-tenant platforms that serve diverse users and partners.

• Familiarity with modern data, experimentation, or AI platforms (e.g., Databricks, Optimizely) or experience building internal developer platforms and tooling that improve team velocity.

• Experience leading through transformation, including evolving business processes and driving adoption of new technologies (such as AI) to enable growth, improve efficiency, and support organizational change.