• Build and maintain product features across backend services, APIs, data systems, and user-facing workflows • Work with product managers, designers, security researchers, and other engineers to ship useful, reliable software • Contribute to services that process SaaS activity, identity data, permissions, alerts, and security findings • Improve existing systems for performance, reliability, maintainability, and observability • Write clear, well-tested code and participate in code reviews and design discussions • Learn unfamiliar parts of the stack and help where the team needs you most • Use AI-powered development tools thoughtfully while reviewing and validating the output

• Design, build, and deploy AI‑powered features and systems within a modern .NET environment. • Own technical direction for AI/ML components, including architecture, model integration, and performance optimization. • Partner with product, engineering, and client stakeholders to shape the roadmap for AI‑driven capabilities. • Evaluate and integrate LLMs, vector search, embeddings, and other modern AI techniques into production workflows. • Lead by example through high‑quality code, strong engineering practices, and thoughtful technical decision‑making. • Drive experimentation, prototyping, and rapid iteration to validate AI‑powered product ideas. • Ensure AI systems are reliable, observable, and maintainable in production environments. • Mentor engineers and contribute to a culture of technical excellence and innovation.

• Own features and system improvements from problem definition through production • Design and build backend services, APIs, data processing workflows, integrations, and product-facing capabilities • Work with product managers, designers, security researchers, and engineers to turn customer needs into shipped software • Improve the performance, reliability, scalability, and observability of existing systems • Make practical technical decisions and explain the tradeoffs clearly • Help raise engineering standards through code reviews, design discussions, mentoring, and documentation • Debug production issues and help teams get to durable fixes, not just short-term patches • Use AI-powered tools effectively while maintaining high standards for correctness, security, and maintainability

• Architect and design digital products using modern tools and technologies • Own and manage the application in production • Participate in inceptions and iteration planning meetings • Lead and participate in standups and retrospectives • Collaborate with cross-product teams and key stakeholders • Establish continuous integration and deployment pipelines • Provide software support in user environments