Intrahealth, a HEALWELL AI Company

Data Engineer

• Analyze and modernize the existing Data Transfer system into a scalable, maintainable .NET-based platform.
• Distill complex business rules into clean, well-architected components while ensuring functional continuity.
• Design, build, test, and deploy backend services for data extraction, transformation, validation, orchestration, and integration.
• Ensure code quality, maintainability, and performance.
• Contribute to architectural decisions, including API design, database schema evolution, modularization, and system scalability.
• Work closely with Product, QA, Architecture, and Support teams to validate functionality, clarify requirements, and ensure successful releases.
• Communicate technical concepts clearly to both technical and non-technical stakeholders.
• Apply coding standards and modern engineering best practices.
• Write and maintain unit and integration tests.
• Investigate and resolve complex data-processing and integration challenges.

Senior Software Developer, Data Platform

DevOps Engineer

• Design, build, and maintain Kubernetes-based infrastructure and cloud environments.
• Own the platform that our development teams build on, ensuring it is reliable, scalable, and secure.
• Build and optimize CI/CD pipelines that enable fast, safe, and repeatable deployments.
• Automate everything from build to production, manual gates are the exception, not the rule.
• Leverage AI coding tools and agentic workflows as a core part of your work to accelerate infrastructure automation, pipeline development, and operational problem solving.
• Define and manage infrastructure using Terraform and related IaC tooling.
• Implement and maintain monitoring, logging, and alerting systems.
• Embed security practices into infrastructure and pipelines.
• Work closely with development teams to remove friction from the delivery process.
• Partner with external infrastructure providers to plan, coordinate, and deliver platform work.

Frontend Engineer

• Design, build, test, and deploy frontend features using React and TypeScript.
• Ensure code quality, maintainability, and performance.
• Help build and refine the systems that build our software.
• Contribute to agentic orchestration pipelines and harness engineering patterns that automate the development lifecycle.
• Investigate and resolve complex technical challenges across the frontend stack.
• Contribute to architectural decisions including component design, state management, API integration patterns, and frontend scalability.
• Develop deep understanding of product functionality and the healthcare workflows it supports.
• Work closely with Product, Architecture, and Support teams to validate functionality, clarify requirements, and ensure successful releases.
• Write and maintain unit, integration, contract, and end-to-end tests. Participate in code reviews and contribute to CI/CD pipeline improvements.

Senior Software Developer, Frontend

Engineering Manager

• Own outcomes for the team: delivery, quality, operability, and predictability.
• Manage commitments, scope, and trade-offs with stakeholders.
• Lead AI-first engineering execution across pods: Define and evolve how work is structured across multiple pods, including ownership boundaries, dependencies, and delivery coordination.
• Establish and scale AI-first development practices across pods, including how engineers use AI tools, agentic workflows, code generation, verification loops, and review discipline.
• Create clear ways of working that support autonomy within pods while maintaining alignment across the broader platform.
• Greenfield AI-first delivery leadership: Help shape and build the engineering organization, systems, and practices required to deliver a new EMR platform from the ground up.
• Drive clarity in ambiguous problem spaces, turning product and technical goals into actionable, testable increments using AI-first development approaches.
• Ensure the team builds systems that maximize engineering leverage through AI, automation, and strong delivery workflows.
• Technical leadership: Guide system architecture and engineering practices across the new platform, including frontend, backend, APIs, and shared services.
• Ensure the new system is scalable, secure, accessible, and maintainable.
• Partner with senior engineers and architects to make sound technical decisions and manage cross-pod technical risk.
• Provide technical leadership on where and how AI-assisted and agentic development should be applied, and where guardrails are required.
• Quality and risk management: Implement CI/CD quality gates (unit/integration/e2e), regression protection, static analysis, dependency controls, and release checks.
• Define and enforce security/privacy-minded practices appropriate for healthcare data.
• Establish guardrails and validation practices so AI-assisted development remains correct, maintainable, and auditable.
• People leadership: Coach engineers and technical leads in AI-first development practices and create a healthy, accountable engineering culture grounded in strong engineering habits (testing, design, PR discipline, operational ownership).
• Support career growth, performance management, and team development across a growing organization.
• Build a learning culture that helps the team keep pace with rapidly evolving AI tooling without destabilizing delivery.
• Cross-functional execution: Partner with Product to shape work into well-specified, testable increments.
• Communicate clearly to technical and non-technical stakeholders, escalating risks early with concrete mitigation.