Solutions Architect, GenAI

Euna Solutions

full-time

Posted on: 9/20/2025

Origin: • 🇺🇸 United States

✨ AI Apply

SeniorLead

AWSAzureCloudKubernetesMicroservices

About the role

Design scalable, secure GenAI infrastructure serving multiple business units
Define integration patterns between GenAI services and existing enterprise systems
Create technical standards and guidelines for AI model deployment and management
Architect data flows for training, fine-tuning, and inference pipelines
Design MCP schemas and integration patterns for AI tool connectivity
Evaluate and recommend GenAI platforms, model serving infrastructure, vector databases
Design model governance frameworks including version control, A/B testing, rollback strategies
Define observability and monitoring approaches for AI system performance and costs
Create disaster recovery and business continuity plans for AI-dependent processes
Translate business requirements from product managers into technical architecture
Partner with security and compliance teams to ensure AI governance standards
Guide engineering teams on implementation patterns and best practices
Communicate technical decisions and trade-offs to non-technical stakeholders

7+ years in solutions architecture, platform engineering, or similar technical leadership roles
Strong background in cloud infrastructure (AWS/Azure)
Experience with API design, microservices architecture, and data pipeline orchestration
Track record of building platforms that scale across multiple teams and use cases
Experience with Model Context Protocol (MCP) implementation or similar tool integration frameworks
Hands-on experience with ML infrastructure, model serving, or data science platforms (strongly preferred)
Familiarity with vector databases, embedding strategies, or search/retrieval systems (strongly preferred)
Experience with containerization, Kubernetes, and DevOps practices (strongly preferred)
Background in regulated industries or environments requiring strong governance (strongly preferred)
Direct experience with LLM APIs, RAG architecture, or prompt engineering automation (nice to have)
Knowledge of MLOps tools and practices (nice to have)
Understanding of AI safety, bias mitigation, or responsible AI practices (nice to have)
Ability to work remote in EST or CST time
Legal ability to work full time in the US (application asks if legally able without visa sponsorship)