Experience Range:
- 7 to 10 years of experience, including substantial hands-on expertise in Azure development, full stack architecture, and AI integration within enterprise platforms
Key Responsibilities:
- 1. Architect and define end-to-end technology solutions across web, API, backend, data, and AI layers, ensuring scalability, resilience, and security
- 2. Lead the design and governance of modern web applications and member portals using responsive UI frameworks and API-first architecture
- 3. Establish and enforce microservices, integration, and event-driven system patterns to enable seamless enterprise and healthcare domain integration
- 4. Drive implementation of conversational AI, Retrieval Augmented Generation (RAG), agentic workflows, and prompt engineering frameworks for intelligent platform experiences
- 5. Architect healthcare domain integrations, including provider directory, benefits eligibility, cost estimation, claims status APIs, and contact center handoff
- 6. Design and implement cloud-native distributed applications on Azure, including CAF-aligned solutions, Kubernetes/OpenShift deployment, and Infrastructure-as-Code strategies
- 7. Establish CI/CD and DevSecOps practices, ensuring robust observability, monitoring, performance, and security across platforms
- 8. Mentor engineering teams on architectural best practices, technical planning, and delivery governance to drive continuous improvement and measurable outcomes
Required Skills:
1. Architectural expertise in Azure cloud-native services
2. Full stack development with Next.js (frontend) and Node.js (backend)
3. Design and orchestration of microservices and API-first architectures
4. Implementation of AI/GenAI solutions, including conversational AI and Retrieval Augmented Generation
5. Experience with Kubernetes (AKS) and Infrastructure-as-Code
6. Integration of healthcare APIs and enterprise systems
Preferred Skills:
1. Hands-on experience with Terraform for Infrastructure-as-Code
2. Knowledge of OpenShift and event-driven architectures
3. Expertise in semantic search and vector retrieval for AI applications
4. Experience in optimizing Large Language Model (LLM) integrations
5. Familiarity with AI guardrails and responsible AI controls
6. Healthcare domain knowledge in provider search, benefits navigation, and contact center integration Desired
Qualifications:
1. Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a closely related discipline
2. Microsoft Certified: Azure Solutions Architect Expert
3. Certification in AI or Machine Learning (such as Microsoft Certified: Azure AI Engineer Associate or equivalent)
