Artificial Intelligence Jobs in North Las Vegas, NV

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

Own and monitor an autonomous robotic fleet at a Las Vegas customer site. Troubleshoot and repair robots, optimize workflows and operational KPIs, conduct testing and validation, analyze throughput and utilization data, provide product feedback, coordinate between customer and internal teams, and help develop deployment procedures and best practices. The role requires onsite work Monday through Friday and physical activity, including lifting up to 50 pounds.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Lead large Microsoft Dynamics 365 (CRM/CE) implementations as a Senior Manager: engage senior clients, design functional solutions, oversee delivery lifecycle, coach teams, refine processes, and ensure operational excellence and adherence to firm standards.

Serve as a Microsoft Dynamics 365 functional lead delivering CRM/ERP assessments, design, configuration, fit-gap analysis, data migration, testing, training, and client-facing implementation support. Lead project tasks, create functional requirements and process flows, support proposals and business development, and coach junior staff to deliver solutions leveraging Microsoft platforms.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Own the full net-new B2B sales cycle, from prospecting and discovery through demos, pilots, negotiations, and closing. Build target account lists, manage pipeline and forecasting in HubSpot, develop relationships across gaming and hospitality markets, attend industry events, and visit Las Vegas properties. Partner with leadership and technical teams to refine messaging, ICP, pricing, qualification, sales stages, and the broader go-to-market playbook. Provide market intelligence and eventually help recruit and develop the sales team.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Manage major infrastructure projects in the energy sector focusing on electric transmission and substation upgrades, ensuring quality and stakeholder satisfaction.

Lead end-to-end delivery of AI and ML services within Managed Services. Manage project planning, budgeting, execution, and quality. Mentor and develop team members, cultivate client relationships, implement model monitoring and operationalization practices, and collaborate with architects and engineers to ensure compliant, reusable AI solutions.

Join a global contributor network supporting flexible AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and verify cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Develop and maintain high-quality technical manuals, guides, specifications, and related documentation. Lead information sessions with subject matter experts, align content with user needs and product requirements, improve existing materials, manage documentation projects, incorporate usability-testing feedback, and coordinate with design teams on visuals and diagrams. Apply documentation tools, industry standards, and best practices to improve clarity, usability, and content quality.

Leads and develops a software engineering team building Libra Solutions’ platforms in an AI-native, agentic delivery model. Owns delivery commitments, technical quality, architecture, code reviews, engineering standards, CI/CD, technical debt, and AI-assisted development practices. Partners with Product, Engineering, and business stakeholders while tracking delivery and system health metrics. Coaches engineers, supports hiring and retention, and establishes responsible AI, prompt engineering, and output-review standards.

Own strategy and roadmap for Crunchbase's customer-facing AI data layer. Identify and validate model-derived data products, lead cross-functional development, set quality standards, drive adoption and monetization, and monitor performance and product economics.

Lead and grow an AI Data Application team to build web services and platforms for metadata storage, dataset generation, and data search. Define technical vision, drive AI adoption in frontend UX, design APIs and query federation, collaborate with ML researchers and data teams, and mentor engineers to accelerate ML pipeline development.