AI Solutions Architect
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Job Location:
Saint Paul, MN - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
This is a remote position.
We are seeking an experienced AI Solutions Architect to design and lead end-to-end AI implementations across enterprise environments. This role focuses on translating business objectives into scalable secure and production-ready AI architectures including LLM applications retrieval-augmented generation systems and advanced machine learning platforms.
You will work closely with executive stakeholders product leaders data teams and engineering groups to design AI solutions that are technically sound operationally scalable and aligned with long-term business strategy.
This is a leadership-level technical role requiring deep architecture experience strong cloud expertise and a practical understanding of AI system deployment.
Key Responsibilities:
Design end-to-end AI system architectures across AWS Azure or GCP
Architect LLM-based solutions including RAG embedding vector search and tool integrations
Define scalable inference and model hosting strategies
Lead design reviews and guide engineering teams through implementation
Establish governance security and compliance standards for AI systems
Design data pipelines and integration patterns for AI workloads
Evaluate model providers frameworks and cost-performance trade-offs
Define monitoring strategies for model performance drift and reliability
Present architectural recommendations to technical and non-technical stakeholders
Drive best practices for AI deployment and lifecycle management
Requirements
Requirements
6 years of experience in solution architecture or senior engineering roles
Strong cloud architecture experience in AWS Azure or GCP
Proven experience designing distributed systems
Experience with LLM applications and RAG architectures
Strong understanding of vector databases and embedding workflows
Experience integrating AI systems with enterprise APIs and data platforms
Experience with containerization (Docker) and scalable deployment patterns
Strong understanding of security IAM and data privacy considerations
Ability to communicate complex technical concepts to executive stakeholders
Advanced / Preferred Qualifications
Experience designing multi-tenant AI platforms
Experience implementing governance and AI risk frameworks
Experience optimizing inference cost and performance
Experience with MLOps and model lifecycle management
Background in data engineering or ML engineering
Experience in regulated industries such as finance or healthcare
Ideal Candidate Profile
The ideal candidate:
Thinks architecturally before coding
Balances innovation with production stability
Understands cost scalability and compliance trade-offs
Has led cross-functional AI initiatives
Can bridge executive strategy and engineering execution
Required Skills:
Experience with AWS Azure or GCP Strong knowledge of networking security and cloud services Experience with Terraform ARM or CloudFormation Familiarity with containers and orchestration tools Strong troubleshooting and optimization skills
Company Industry
IT Services and IT Consulting
Key Skills
- Organizational Management
- Presentation Skills
- Agile
- SAFe
- AWS
- Solution Architecture
- Conflict Management
- Data Management
- Scrum
- Team Management
- Pre-sales
- Management Consulting
