Senior Solutions Architect – AI & Automation

White Cap

. Define, design, and oversee systems and applications architecture for current and future business applications .

Posted 9/23/2026full-timeRemote • Florida • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing AI solutions, including proficiency with Databricks and modern AI frameworks. Capable of establishing architecture standards and providing technical leadership throughout the solution lifecycle.

Highest-signal resume keywords

AI Solution Design and ImplementationDatabricks ExperienceTechnical Leadership and MentoringAzure DevOps Best PracticesArchitecture Standards Establishment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML WorkloadsGenAI CapabilitiesDatabricks AppsLakehouse ArchitectureModel Context Protocol (MCP)Agent-Based ArchitecturesIntelligent Workflow AutomationCloud-Based SolutionsReusable FrameworksTechnical Standards Creation

Soft Skills

TroubleshootingProblem-Solving

Tools & Technologies

Microsoft Copilot StudioMicrosoft Copilot ExtensibilityAgent BuilderEnterprise Data PlatformsAPIsSaaS Applications

Industry Keywords

Architecture PatternsEngineering PracticesProof-of-ConceptsPrototypesAcceleratorsReference Implementations

Tech Stack

Tools & technologies

AzureCloudUnity

About the role

Key responsibilities & impact

Define, design, and oversee systems and applications architecture for current and future business applications
Evaluate new and emerging technologies and development methodologies for faster, cost-effective, and reliable solutions
Partner with infrastructure, application, and quality teams to ensure applications meet business requirements, are documented, and have ongoing support and maintenance processes
Drive efficient applications and infrastructure design by aligning infrastructure roadmaps with application technology strategy, hardware vendor roadmaps, and service capabilities
Identify and evaluate emerging technologies for strategic organizational fit
Contribute to technology strategy through requirements gathering, collecting deployment plans, synthesizing business goals, and defining operating strategies
Design, prototype, and validate AI and automation solutions
Establish reusable architecture patterns, technical standards, and engineering practices for enterprise-scale adoption
Build proof-of-concepts, prototypes, accelerators, and reference implementations
Mentor development teams and provide technical leadership from concept through production deployment
Manage a group or team of professional individual contributors and/or indirectly supervise support staff

Requirements

What you’ll need

Typically requires BS/BA in a related discipline
Generally requires 7+ years of experience in a related field
Advanced degree may offset less experience in some disciplines
Experience designing and implementing AI solutions using Databricks, including AI/ML workloads, GenAI capabilities, Databricks Apps, Unity Catalog, and Lakehouse architecture
Experience designing, building, and deploying AI-powered applications and intelligent agents using enterprise data platforms and modern AI frameworks
Experience integrating AI solutions with enterprise data platforms, APIs, SaaS applications, and business systems
Hands-on experience with Microsoft Copilot Studio, Microsoft Copilot extensibility, Agent Builder, and agent-based architectures
Experience with Model Context Protocol (MCP), agent orchestration patterns, and intelligent workflow automation
Knowledge of RAG, prompt engineering, grounding techniques, memory patterns, and human-in-the-loop solution design
Ability to establish architecture standards, reference architectures, reusable design patterns, and implementation frameworks
Experience balancing innovation, security, scalability, maintainability, and operational excellence
Experience creating technical standards and architectural guidance for emerging technologies and AI-enabled solutions
Ability to evaluate new technologies and determine practical enterprise adoption strategies
Experience designing, building, and deploying production AI, automation, and cloud-based solutions
Experience building proof-of-concepts, prototypes, accelerators, and reference implementations
Experience mentoring development teams and providing technical leadership throughout the full solution lifecycle
Strong troubleshooting and problem-solving capabilities across AI, data, cloud, and automation platforms
Experience implementing Azure DevOps best practices, including source control, branching models, CI/CD pipelines, release management, and environment management
Experience establishing software engineering standards and delivery practices
Experience developing reusable frameworks, templates, and technical accelerators

Benefits

Comp & perks

Career opportunities within a diverse work environment
Overnight travel typically less than 10% of the time