AI Fullstack Engineer

Ascendion Engineering; Hyderabad, Chennai District, Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Ascendion Engineering seeks an AI Solutions / AI Fullstack Engineer in India to join a mission-critical healthcare cloud-native initiative. You will collaborate with stakeholders to translate complex workflows into scalable AI-enabled applications, spanning frontend, backend, APIs, data platforms, and secure deployments.

The role requires 7–12 years of experience with Python, .NET, C#, ReactJS, and hands-on AI/LLM frameworks.

Qualifications

• 7–12 years of experience in software/AI engineering.
• Healthcare domain knowledge in payer/provider workflows is desirable.
• Experience building cloud-native solutions and AI-enabled software.

Responsibilities

• Partner with healthcare stakeholders to understand workflows and objectives.
• Translate needs into scalable cloud-native tech solutions.
• Design enterprise architecture for frontend, backend, APIs, data platforms and AI features.
• Develop production-grade software using .NET, Python, APIs, microservices.
• Drive cloud engineering, DevOps, CI/CD, IaC, automation and monitoring.
• Leverage AI/LLMs and RAG to enhance healthcare operations and outcomes.
• Identify modernization opportunities and propose innovative solutions.
• Own full solution lifecycle from discovery to production support.
• Mentor teams and uphold engineering standards.

Skills

Python

AI/ML

RAG

C#

.NET

LLMs

GenAI frameworks

Azure AI Services

ReactJS

US Healthcare domain

Tools

Azure

Kubernetes

CI/CD

Job description

Job Title: AI Solutions / AI Fullstack Engineer

Location: Pune, MH / Bangalore, KA / Chennai, TN / Hyderabad, TG

Work Hours: 2 PM - 11 PM IST

Notice: Immediate - 30 Days Joiner

Experience: 7 - 12 Years

Mandate Skillset: Python, AI/ML experience, RAG, C#, .Net, LLMs, GenAI Frameworks (LangGraph / Lang Chain / Llama Index / AutoGen / Crew AI / Hugging Face), Azure AI Services, ReactJs and US Healthcare (Domain Expertise)

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.

Domain Skills

• Strong expertise in healthcare payer/provider domains such as Member Enrollment & Eligibility, Claims Processing & Adjudication, Provider Management, Healthcare EDI (HIPAA X12 Transactions), Benefits Administration, Prior Authorization, Care Management (CM), Utilization Management (UM), Disease Management (DM), Clinical Operations, Grievance & Appeals (G&A), Payment Integrity.
• Experience with healthcare interoperability standards such as HL7/FHIR, APIs, and healthcare data exchange patterns is preferred.

Technical Skills

• Full Stack Engineering including fullstack application development, .NET / C#, Python, REST APIs & Microservices, Modern Frontend Frameworks, SQL / NoSQL databases, event driven architecture
• Cloud & DevOps expertise in Azure Cloud Architecture, cloud native application development, Azure DevOps / GitHub Actions, CI/CD automation, containers & Kubernetes, Infrastructure as Code, security, performance, and scalability engineering
• AI & Intelligent Engineering skills such as AI/LLM solution design and implementation, generative AI applications, agentic AI workflows, Retrieval Augmented Generation (RAG), intelligent automation, AI enabled software engineering practices