Hands-On AI Architect — Remote/Hybrid, Client-Facing

Crowe; Fort Wayne (IN); Hybrid; USD 102,000 - 204,000; Full time

Benefits offered by this job

Unlimited PTO

Flexible remote work policy

Job summary

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to lead hands-on AI solution design and production deployments for clients. You will own architecture, feasibility, and quality, while mentoring engineers and guiding technical decisions across Azure, AWS, and GCP environments.

In this role you’ll work closely with client teams, translate complex challenges into scalable AI applications, and ensure production readiness with secure, reliable deployments.

Qualifications

• Bachelor's degree in CS/engineering or related field.
• Minimum 6 years in production software, cloud, or AI/ML engineering.
• Hands-on engineering with production-grade solutions.
• Experience architecting cloud-native apps on Azure/AWS/GCP.
• Willingness to travel up to 80%.

Responsibilities

• Architect and develop end-to-end AI solutions including generative AI and RAG.
• Lead solution architecture for AI build and POC engagements.
• Remain hands-on across solution development and prototyping.
• Design cloud-native AI solutions on Azure, AWS, and GCP.
• Define patterns for LLMs, vector databases, APIs, microservices, and data platforms.
• Mentor engineers and lead Architecture Review Board processes.

Skills

Hands-on software engineering

Solution architecture

Cloud-native architectures

Mentoring engineers

Client-facing skills

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field

Tools

Azure

AWS

GCP

LLMs

Job description

Crowe Studio is seeking a Forward Deployed AI Architect (Manager) to lead hands-on AI solution design and production deployments for clients. You will own architecture, feasibility, and quality, while mentoring engineers and guiding technical decisions across Azure, AWS, and GCP environments.

In this role you’ll work closely with client teams, translate complex challenges into scalable AI applications, and ensure production readiness with secure, reliable deployments.