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AI Architect
Schneider Geospatial, LLC. Champion AI adoption across Engineering by challenging existing practices and identifying opportunities to improve productivity, quality, and delivery speed .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing AI architectures, focusing on production-ready solutions that enhance engineering productivity and quality. Proven ability to mentor teams and drive AI adoption while aligning technical efforts with business objectives.
Highest-signal resume keywords
AI Architecture DesignProduction LLM ApplicationsCloud ArchitectureAgentic Workflows ImplementationAzure Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Solutions DevelopmentMachine Learning DeploymentData IntegrationAPIsSoftware DevelopmentSecurity StandardsObservabilityCost ManagementEngineering StandardsTechnical Change Management
Soft Skills
CommunicationCollaborationMentoringInfluencing Without AuthorityProblem Solving
Tools & Technologies
Azure.NET/C#TypeScriptRelational DatabasesVector DatabasesHybrid SearchContainersOpen-Source AI ModelsEnterprise SecurityAI-Enabled Development
Industry Keywords
AI AdoptionEngineering ModernizationGovernanceReusable Engineering FrameworksOperational Automation
Tech Stack
Tools & technologiesAzureCloudTypeScript.NET
About the role
Key responsibilities & impact- Champion AI adoption across Engineering by challenging existing practices and identifying opportunities to improve productivity, quality, and delivery speed
- Collaborate across AI, Data, Product, and Engineering to translate priorities into scalable, production-ready solutions
- Align implementation efforts to accelerate delivery and reduce duplication
- Design production-ready AI architectures, including model integration, RAG, agent orchestration, and data integration
- Emphasize reusable services, interoperability, and engineering standards
- Implement agentic workflows and AI-enabled development and testing practices
- Prototype solutions, guide implementation, resolve technical challenges, and remove barriers to engineering progress
- Implement security, privacy, governance, evaluation, observability, and cost-management standards
- Influence engineering teams, challenge conventional thinking, mentor developers, and build internal AI champions
- Track improvements in engineering efficiency, solution quality, reliability, and cost while connecting technical outcomes to customer and business value
- Work across technical and product teams to shape architecture, accelerate innovation, and build reusable capabilities
Requirements
What you’ll need- Proven experience designing, building, deploying, and operating AI or machine learning solutions in production
- Deep practical expertise in production LLM applications, retrieval, orchestration, and emerging AI technologies
- Strong hands-on engineering capabilities across cloud architecture, APIs, data platforms, security, and modern software development
- Experience implementing agentic workflows that deliver measurable improvements in engineering productivity, efficiency, or cost
- Demonstrated ability to translate product and business requirements into practical, scalable technical solutions
- Track record of driving technical or organizational change with urgency, accountability, and the ability to influence without direct authority
- Strong architectural judgment balancing speed, scalability, security, quality, and cost
- Excellent communication, collaboration, and mentoring skills, with the ability to partner effectively across Engineering, Product, and other technical functions
- Experience across hosted and open-source AI model ecosystems
- Experience establishing enterprise AI architecture, governance, and reusable engineering frameworks
- Experience applying AI to software development, quality engineering, and operational automation
- Experience leading engineering modernization or AI adoption initiatives across multiple teams
- Ability to connect technical investments to engineering efficiency, customer value, and business performance
- Experience with Azure, .NET/C#, TypeScript, relational and vector databases, hybrid search, containers, and enterprise security
Benefits
Comp & perks- Competitive salary
- Comprehensive benefits
- Mission-driven work helping local governments better serve their communities
- Opportunity to shape Schneider's AI architecture and advance engineering capabilities across the organization
- Opportunity to drive meaningful change in software development, testing, and delivery
- Collaborative, growth-oriented environment
- Opportunity to make a lasting impact