• Design and implement algorithms for real-time control of microgrid components. • Collaborate with partner teams and equipment suppliers. • Translate system requirements and specifications into efficient, safe, and maintainable embedded controls code • Define and execute validation procedures to ensure controller compliance with utility interconnection agreements and ancillary market requirements when grid-connected. • Support controller verification through simulation, testing, and field validation. • Set up and maintain code repositories, build tools, and CI/CD workflows • Implement unit tests integration tests, and hardware abstraction layers to support scalable development • Contribute to clear documentation of software behavior, interfaces, and design assumptions. • Participate in code reviews to improve reliability, safety, and overall software quality. • Support debugging of unexpected controller behavior before and after deployment, including field data analysis and log review.

• Improve CI/CD pipelines to ensure consistent and quality deployments across various environments, fully automating releases across all pieces of the maxRTE application. • Design and implement auto scaling and cost-effective AWS ECS/EKS solution for migration of key pieces of maxRTE product structure. • Design and implement enhanced task queueing system to accompany containerized application implementation. • Help implement automated testing solutions to ensure quality via coverage of 100% of codebase. • Help design and implement migration to microservice architecture with templated, repeatable infrastructure for scalability and efficiency in developer experience. • Expand on containerized infrastructure to utilize kubernetes w/ Argo CD or similar application implemented for data processing, report generation, APIs, and much more. • Mentor junior developers, fostering a culture of learning and knowledge sharing. • Collaborate with cross-functional teams to gather requirements and implement solutions that align with product goals. • Careful and well thought out design capability - considering timeframes, available resources, cost of implementation, and short and long term solutions as potential outcomes. • Highly effective prioritization capability - using learned knowledge of products, clients, and internal/external processes to consistently focus attention where it's needed most

• Design and develop event-driven, data-intensive backend services using Node.js, TypeScript, AWS, and cloud-native technologies to support AI workloads at scale. • Architect and implement microservices-based solutions with clearly defined service boundaries, REST APIs, and asynchronous messaging patterns. • Lead the development and deployment of AI-enabled systems that process structured and unstructured data to support intelligent decision-making. • Drive Test-Driven Development (TDD) practices and maintain automated testing strategies across unit, integration, and contract testing. • Design scalable cloud-native architectures and distributed systems that support mission-critical healthcare applications. • Collaborate with product owners, engineers, and stakeholders to translate business requirements into production-ready technical solutions. • Evaluate emerging AI technologies, frameworks, and tools to support innovation, modernization, and long-term scalability. • Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

• Build and maintain features across our full stack (Ruby on Rails, React, Flutter), taking end-to-end ownership from initial design through production. • Act as a product-minded partner, translating complex user needs—often in early or ambiguous stages—into intuitive, technically sound solutions. • Operate with high autonomy, driving architectural decisions and navigating ambiguity to solve impactful engineering challenges. • Elevate our engineering culture by setting high standards, mentoring teammates, and simplifying processes to help the team move faster as we scale. • Proactively balance feature velocity with long-term system health by identifying and addressing technical debt before it becomes a bottleneck. • Prioritize pragmatic simplicity, ensuring we build only what is necessary to validate assumptions and deliver value, while resisting complexity that hinders agility. • Ensure the reliability and performance of our critical systems by taking ownership of production issues and implementing sustainable fixes.