Claims Solution Architect
Role: Claims Assist Solution Architect
Location: Atlanta, GA (Hybrid – 3 days onsite mandatory) Duration: 10 Months Visa: Open to eligible candidates Note: Candidates with prior AIG experience will be given strongpreference Position Overview We are looking for a seasoned Solution Architect with deep
experience in the insurance domain, specifically in claims and underwriting
systems. The ideal candidate should bring strong architectural expertise along
with hands-on technical experience across enterprise integration and cloud
environments. Must-Have Experience & Skills Minimum 10+ years of overall IT experience , including significant architecture
exposure At least 5+ years in the insurance domain with hands-on
involvement in claims systems
- Prior experience working with AIG platforms/systems is highly
preferred
- Strong background in designing end-to-end enterprise solutions across On-Prem
and AWS Cloud environments
- Proven experience with integration technologies such as MuleSoft, API
Gateways, REST APIs, and RabbitMQ
- Experience working with modern UI frameworks such as React.js
- Strong understanding of SQL and NoSQL databases , including exposure
to modern data platforms
- Experience operating within Agile SDLC frameworks and
DevOps/DevSecOps environments Key Responsibilities
- Design and define scalable solution architectures aligned with business and
technology objectives
- Lead architectural discussions for claims-related systems and enterprise
integrations
- Develop architecture artifacts including solution blueprints, sequence diagrams,
data flow diagrams, interface specifications, and data models
- Collaborate with business stakeholders, technology teams, and cross-functional groups
to ensure solution alignment
- Present architecture strategies and design decisions to leadership and stakeholder
teams
- Support secure, scalable, and high-performance system implementations Nice to Have Exposure to Generative AI concepts, especially RAG (Retrieval-Augmented
Generation)
- Hands-on experience implementing AI-driven enhancements within enterprise workflows
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