Cloud-Native Solutions Architect — AI/LLM & AWS (Remote)

IRIS KPO Resourcing; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote work

Job summary

IRIS KPO Resourcing is seeking a Software Solution Architect to guide delivery teams across frontend, backend and platform layers. The role emphasizes translating architecture into practical designs and ensuring consistent implementation within a cloud-native, AWS-based environment.

The ideal candidate combines senior engineering experience with hands-on architectural delivery, capable of collaborating with multiple teams and driving end-to-end solution design, including AI/LLM considerations.

Qualifications

• Strong senior engineering background or early architecture experience.
• Experience with cloud-native systems (AWS preferred).
• Understanding of distributed, event-driven, and full-stack architectures, including frontend integration patterns.
• Ability to convert architecture into implementable designs.
• Clear communication across technical and non-technical audiences.

Responsibilities

• Produce clear, implementable solution designs and architecture artefacts.
• Translate high-level architectural direction into concrete designs.
• Ensure alignment with established principles and standards.
• Contribute to architecture backlog and design refinement.
• Support architectural consistency across frontend, backend, and platform components.

Skills

Architectural design

Cloud-native

AWS

LLM integration

End-to-end system thinking

Tools

Terraform

APIs

Job description

IRIS KPO Resourcing is seeking a Software Solution Architect to guide delivery teams across frontend, backend and platform layers. The role emphasizes translating architecture into practical designs and ensuring consistent implementation within a cloud-native, AWS-based environment.

The ideal candidate combines senior engineering experience with hands-on architectural delivery, capable of collaborating with multiple teams and driving end-to-end solution design, including AI/LLM considerations.