AI/Data Solutions Architect

AmeriVet•San Antonio, TX

1d•Hybrid

About The Position

Amerivet is looking for a AI/Data Solutions Architect who can lead the design of scalable analytics, reporting, and AI-enabled solutions across the organization. This role will sit at the intersection of AI solutions design, data architecture, BI architecture and business analytics. The ideal candidate will have strong hands-on experience with Microsoft Fabric, Power BI, Python, Claude, RAG frameworks, token optimization, and MCP server concepts. This individual should be able to design modern data and AI solutions, partner with business stakeholders, and help move AI-enabled analytics from concept to production.

Requirements

Microsoft Fabric
Power BI
Python
Claude
OpenAI
Generative AI / LLMs
RAG frameworks
Prompt engineering
Token optimization
MCP server concepts
Data modeling and semantic layer design
SQL and analytical data structures
Dashboard design and KPI development
Data governance and reporting standardization
API-based data and AI integrations
5+ years of experience in data architecture, analytics architecture, BI architecture, AI architecture, or related roles.
Strong hands-on experience with Power BI, data modeling, semantic models, and dashboard delivery.
Strong understanding of Microsoft Fabric or modern cloud-based analytics platforms.
Practical knowledge of AI, LLMs, RAG patterns, and enterprise AI use cases.
Experience working directly with business stakeholders to define metrics, requirements, and solution architecture.
Ability to design scalable, governed, and production-ready data and AI solutions.
Strong analytical thinking, problem-solving, communication, and documentation skills.
Ability to operate independently and lead solution design from concept to delivery.

Nice To Haves

Claude / Anthropic certification preferred.
Experience building production-grade AI or GenAI solutions.
Experience with vector databases, embeddings, semantic search, and enterprise knowledge retrieval.
Experience with enterprise AI governance, model evaluation, and cost monitoring.
Experience with Azure AI, Azure OpenAI, or related cloud AI services.
Familiarity with agentic AI frameworks, tool calling, workflow orchestration, and AI-assisted analytics.
Experience supporting executive, finance, operations, clinical, & business performance analytics.

Responsibilities

Design and support AI-enabled analytics use cases using Claude, OpenAI, Python, and modern LLM frameworks.
Build or support RAG-based solutions that connect enterprise data, documentation, and business context to LLM-powered workflows.
Identify opportunities where AI can improve analytics, reporting, automation, decision intelligence, and business productivity.
Apply best practices for prompt engineering, context management, model selection, token optimization, and cost control.
Help define scalable, secure, governed, and production-ready AI solution patterns.
Support AI governance practices including responsible usage, data privacy, access controls, auditability, and documentation.
Support architecture and implementation of MCP server-based integrations where applicable.
Help design AI agents and assistant workflows that can securely interact with enterprise tools, reporting assets, data sources, and documentation.
Collaborate with engineering teams to define tool access, retrieval logic, orchestration patterns, and integration standards.
Design scalable data, BI, and analytics architecture using Microsoft Fabric, Power BI, and modern cloud-based data platforms.
Build and guide the development of semantic models, curated datasets, reporting layers, and enterprise analytical data structures.
Lead the architecture and design of Power BI reporting solutions, dashboards, and self-service analytics capabilities.
Define best practices for data modeling, metric standardization, data governance, reporting architecture, and BI platform development.
Partner with business and technical teams to translate strategic requirements into scalable data and analytics solutions.
Support enterprise KPI frameworks, executive dashboards, operational reporting, and reusable reporting patterns.