• Architect and ship AI-driven features — RAG pipelines and agentic workflows that take action across systems with human oversight where it matters. • Build the backend and infrastructure to run these reliably and at scale, across tens of thousands of IoT devices and low-connectivity environments. • Define what "good" looks like for our AI systems — holding them to real accuracy and impact standards, not demo performance. • Own large parts of the system end-to-end, from architecture to production reliability. • Work closely with product and data science to iterate fast and keep solutions aligned with product vision and real public-health needs.

• Develop tools that leverage generative AI along with our technology solutions to assemble functional demos of government digital services for a variety of government programs • Design and implement example applications using our open source platforms that can be demonstrated to potential clients in bids and conferences • Support project teams in using our platforms and iterate based on their feedback

• Design and implement a shared core layer used across desktop, mobile, and backend • Contribute to architecture decisions around CRDT and distributed systems • Collaborate closely with frontend, mobile, and backend engineers to integrate Rust components • Improve performance, reliability, and maintainability of the system

• Design and develop responsive, modular Angular applications using TypeScript and modern front-end best practices. • Implement reusable UI components using HTML5, CSS/LESS/SCSS, and reactive programming patterns with RxJS. • Manage application state using NgRx or similar state management libraries. • Develop scalable and secure ASP.NET Core Web APIs using clean architecture principles. • Write maintainable and testable C# code following SOLID principles. • Build automated unit and integration tests using tools such as Jest and xUnit. • Design and optimize relational database schemas and queries for SQL Server or PostgreSQL. • Work with MongoDB when NoSQL data storage is required. • Deploy and maintain applications on AWS infrastructure, including compute, storage, and event-driven services. • Implement event-driven architectures using services like SNS and SQS. • Configure cloud resources such as API Gateway, IAM policies, and CloudWatch monitoring. • Containerize applications using Docker and support CI/CD pipelines for automated deployment. • Collaborate with DevOps teams to ensure reliable infrastructure and deployment workflows. • Participate in architecture discussions, code reviews, and agile development processes.