Experience: 12+
Location: Louisville, KY
visa: Independent only
AI Solution Architecture
• Design end to end AI/ML and GenAI architectures, covering data ingestion, model development, deployment, monitoring, and lifecycle management.
• Define reference architectures for LLMs, RAG, agentic workflows, predictive models, and automation use cases.
• Ensure scalability, reliability, performance, and cost optimization of AI platforms across cloud and hybrid environments. 2
Enterprise & Cloud Integration
• Integrate AI solutions with enterprise systems, APIs, data platforms, and cloud services.
• Align AI architecture with broader enterprise architecture, security, and DevOps standards.
• Guide teams on AI ready cloud patterns (containers, MLOps, CI/CD, observability). 3
Governance, Security & Compliance
• Work with central AI COEs and governance bodies to define guardrails, approval workflows, and audit processes for AI usage.
• Ensure responsible AI principles: data privacy, model explainability, bias mitigation, and regulatory compliance.
• Enforce security best practices including identity, access control, secrets management, and model protection. 2
Business & Stakeholder Collaboration
• Partner with business leaders to identify AI opportunities, define backlogs, and translate business problems into AI solutions.
• Provide architectural leadership during pre sales, proposals, and solution reviews.
• Act as a trusted advisor on AI feasibility, ROI, and risk assessment. 2
Technical Leadership & Enablement
• Mentor architects, data scientists, and engineers on AI design patterns and best practices.
• Review solution designs, conduct architecture boards, and ensure delivery quality.
• Contribute to internal accelerators, reusable assets, and AI capability building. 1
Required Skills & Experience
Technical Skills
• Strong understanding of AI/ML concepts, including supervised/unsupervised learning, deep learning, NLP, and GenAI.
• Hands on experience with LLMs, prompt engineering, RAG architectures, vector databases, and AI APIs.
• Expertise in cloud platforms (Azure, AWS, or Google Cloud Platform) and AI services.
• Knowledge of data engineering, APIs, microservices, containers, and DevOps/MLOps.
• Experience with monitoring, logging, model performance tracking, and cost controls. 2
Architecture & Design
• Proven experience designing large scale, distributed, and secure enterprise systems.
• Ability to create architecture diagrams, design documents, and implementation roadmaps.
• Strong grasp of non functional requirements: scalability, availability, resilience, and security. 3
Experience
• Typically 10+ years in software/solution architecture, with 3–5+ years focused on AI/ML or data driven solutions.
• Experience working in regulated or large enterprise environments is preferred.
(Exact years may vary based on organization standards; not explicitly defined in sources.)
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