AI/ML/Gen AI Engineer
AI/ML/Gen AI Engineer
ascendionFresher
- Posted 21 days ago
- Over 100 applicants have applied
Job Description
About the Role
Job Title: Healthcare AI Solution Engineer / Mid-FDE
Responsibilities:
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.
- 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.
- Experience with healthcare interoperability standards such as HL7/FHIR, APIs, and healthcare data exchange patterns.
- Not specified.
More Info
Key Skills
generative AI applications
Infrastructure as Code
NoSQL databases
AI-enabled software engineering practices
CI CD automation
GitHub Actions
Azure Cloud Architecture
modern frontend frameworks
AI LLM solution design and implementation
agentic AI workflows
intelligent automation
event-driven architecture
cloud-native application development
Containers
About Company