• Design, build, and maintain scalable backend services, APIs, and data systems • Contribute to frontend application development using modern web technologies • Collaborate cross-functionally with Product, Design, AI, and Engineering teams to ship high-impact product improvements • Improve system reliability, observability, performance, and developer tooling • Help shape technical direction, architecture decisions, and engineering best practices • Investigate and resolve complex production issues across the stack • Prototype quickly, gather feedback, and iterate based on customer and business needs • Mentor developers through collaboration, code reviews, and technical discussions

• Design and build scalable backend systems for a high-performance SaaS product • Architect and implement RESTful APIs to support web and product features • Translate product requirements into efficient system and database designs • Optimize system performance for speed, scalability, and reliability • Design data flow across services involving search, caching, and asynchronous processing • Build and maintain secure and reliable cloud-based infrastructure on AWS • Implement and manage containerized services for deployment and scaling • Ensure system observability through logging, monitoring, and error tracking • Collaborate with product and engineering teams to define technical solutions • Participate in architecture decisions for scaling multi-tenant SaaS systems • Identify bottlenecks in existing systems and implement performance improvements • Ensure code quality through reviews, testing practices, and engineering standards

• Set technical direction for your area - make build-vs-buy decisions, define architecture, and own the technical roadmap alongside product leadership. • Take ambiguous problems and make them concrete - scope work, identify risks, break down large initiatives into deliverable increments, and drive alignment across teams. • Design and deliver production-grade systems - scalable pipelines, robust services, and high-performance solutions that serve real users at scale. • Leverage AI tools as part of your workflow - you use AI-assisted development (Claude Code, Cursor, Copilot) to accelerate your work and have formed opinions on when it helps and when it gets in the way. • Evaluate and integrate AI/ML capabilities into production systems when the problem calls for it - you don't need to be an ML researcher, but you're sharp enough to pick up LLMs, embeddings, or classification models and put them to work. • Drive cross-team technical initiatives - influence engineers and teams you don't manage. Lead RFCs, drive architectural reviews, and build consensus on hard technical decisions. • Own what you build - from requirements to release to production. You build it, you run it. You monitor SLOs/SLIs, troubleshoot production issues, and continuously improve reliability. • Raise the engineering bar - through code reviews, mentorship, technical documentation, and by modeling the standards you expect from others.

• The Technical Lead supports the design and implementation of interoperable public health data exchange and AI solutions. • Responsible for the technical design and execution of data exchange, interoperability, and AI/ML solutions supporting surveillance, reporting, analytics, and related public health use cases. • Responsible for overall QA/QC and troubleshooting solutions encountered across the tech stack. • Lead architects, engineers, analysts, and informaticists to translate client needs into technical approaches. • Support the application of interoperability standards such as HL7 v2, FHIR, CDA, APIs, and terminology systems within public health contexts. • Lead technical discussions, design sessions, and reviews; help document decisions, assumptions, and dependencies. • Review technical deliverables and documentation for alignment with scope, requirements, and quality expectations. • Identify technical considerations related to integration, security, privacy, onboarding, and data-sharing constraints, and discuss potential mitigation options with the team. • Support integration testing, validation, and exchange troubleshooting activities when applicable. • Share technical knowledge and lessons learned across projects and support mentoring of junior staff.