Role Description As a Senior Software Engineer, you will join an innovative and collaborative team focused on building, scaling, and optimizing modern healthcare platforms. You will play a key role in designing high-quality software architectures, creating serverless API integrations, and deploying microservices within state-of-the-art containerized environments. Working primarily with C#, Microsoft Azure, Azure Functions, and Azure Kubernetes Service (AKS), you will help develop systems that enhance operational performance and support critical patient and clinical outcomes. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities - Design, write, test, and maintain high-quality, scalable code using C# and modern .NET frameworks - Develop and configure cloud services, focusing on Azure Functions, serverless architectures, and robust API endpoints - Deploy, manage, and orchestrate containerized microservices within Azure Kubernetes Service (AKS) - Collaborate closely with architects, product owners, and engineering peers to transform complex business requirements into high-performing technical solutions - Maintain and optimize continuous integration and continuous deployment (CI/CD) pipelines to support rapid, secure software releases - Use enterprise-approved AI tools to streamline workflows, automate repetitive development tasks, and drive continuous improvement in engineering velocity - Evaluate emerging technical trends to inform solution design, optimize code performance, and foster strategic innovation - Perform peer code reviews, champion engineering best practices, and provide technical guidance to team members - Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI Qualifications - Bachelor's degree in Computer Science, Software Engineering, or a related technical field OR having equivalent experience - 6+ years of professional software engineering experience using C# and .NET frameworks - 3+ years of experience designing and deploying cloud-native applications on Microsoft Azure (including Azure Functions or similar serverless components) - 3+ years of experience designing, developing, and integrating RESTful APIs and microservice architectures - 1+ years of hands-on experience orchestrating and managing containerized deployments using Azure Kubernetes Service (AKS) or equivalent Kubernetes-based container technologies - 1+ years of Terraform experience Requirements - Official Microsoft Azure certifications (e.g., Azure Developer Associate, Azure DevOps Engineer, or Azure Solutions Architect) - Strong experience designing, configuring, and executing automated CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) - Experience working with both relational databases (SQL Server) and NoSQL databases (Cosmos DB) including query optimization - Excellent understanding of Agile/Scrum delivery frameworks and software security best practices (OAuth, API Gateway security) - Experience working with UI technologies such as Angular, React, Vue or similar technologies - 1 year of experience in AI, Python, Langchain - 1 year of experience working with Codex, Copilot Benefits - Comprehensive benefits package - Incentive and recognition programs - Equity stock purchase - 401k contribution (all benefits are subject to eligibility requirements)

• Design and develop AI-driven applications, including single and multi-agent workflows • Build and maintain full-stack solutions (frontend and backend components) • Leverage AI tools and agentic coding practices to accelerate development • Develop orchestration logic for agent-based systems and workflows • Integrate LLM-based capabilities such as document processing, embeddings, and retrieval • Implement best practices for AI evaluations to ensure quality and prevent regressions • Contribute to and maintain CI/CD pipelines and deployment processes • Collaborate with architects and engineering leadership on solution design and standards • Continuously improve development practices and contribute to evolving AI engineering frameworks

• Build the platform foundation, including the MCP Gateway and shared RAG services. • Set technical direction through design documents and ship the components yourself. • Own reliability, observability, and developer ergonomics. • Track the AI tooling ecosystem and feed signal back into the roadmap. • Carry services end-to-end.

• Owning product-level AI solution design and delivery in collaboration with the AI Architect • Building RAG pipelines using EHR data, claims, and clinical text using embeddings and vector search • Developing, fine-tuning, and evaluating LLMs and classical ML models with robust guardrails • Establishing and operating MLOps infrastructure, including experiment tracking, CI/CD, and drift monitoring • Managing reliability, security, and cost for your product’s AI services, including SLOs and incident response • Ensuring HIPAA compliance and responsible AI practices are embedded across development and operations • Reviewing code and experiments with an emphasis on reproducibility - mentoring engineers and data scientists on the team • Contributing reusable AI components back to the shared platform and leveraging GitHub and Microsoft Copilot to improve team productivity