Ascendion
Website:
ascendion.com
Company:
https://www.linkedin.com/company/ascendion
Seniority: Not Applicable
Industries: Technology, Information and Internet
Job details:
About the Role"
"Job Title": Healthcare AI Solution Engineer / Mid-FDE
"Responsibilities":
- Partner directly with healthcare business stakeholders to understand workflows, challenges, and strategic objectives across payer operations.
- Translate business needs into scalable, secure, cloud-native technology solutions.
- Design enterprise solution architecture and build end-to-end applications across frontend, backend, APIs, integrations, data platforms, and AI capabilities.
- Develop production-grade software using .NET, Python, modern frameworks, microservices, APIs, and engineering best practices.
- Drive cloud engineering, DevOps, CI/CD, Infrastructure as Code, automation, monitoring, and operational excellence.
- Leverage AI/LLMs, intelligent agents, and automation to improve healthcare operations, engineering productivity, and business outcomes.
- Identify modernization opportunities and proactively recommend innovative solutions.
- Own the complete solution lifecycle—from discovery, architecture, design, development, testing, deployment, and production support.
- Mentor engineering teams and establish engineering excellence through architecture standards, coding practices, and innovation.
"Required Skills":
- Strong expertise in one or more healthcare payer/provider domains.
- Experience with healthcare interoperability standards such as HL7/FHIR, APIs, and healthcare data exchange patterns.
- Full Stack Engineering skills including .NET / C#, Python, REST APIs & Microservices, modern frontend frameworks, SQL / NoSQL databases, and event-driven architecture.
- Cloud & DevOps skills such as Azure Cloud Architecture, cloud-native application development, Azure DevOps / GitHub Actions, CI/CD automation, Containers & Kubernetes, Infrastructure as Code, and security, performance, and scalability engineering.
- AI & Intelligent Engineering skills including AI/LLM solution design and implementation, generative AI applications, agentic AI workflows, retrieval augmented generation (RAG), intelligent automation, and AI-enabled software engineering practices.
"Desirable Skills":
- Experience with healthcare interoperability standards such as HL7/FHIR, APIs, and healthcare data exchange patterns.
"Education Qualification":
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