Top Artificial Intelligence Jobs in Charlotte, NC

Develop AI-enabled software solutions for internal digital transformation initiatives. Design, code, test, debug, and support scalable applications using modern engineering practices. Apply machine learning tools, automate workflows, analyze data, contribute to APIs, microservices, and cloud-native architecture, and translate business requirements into technical designs. Review junior team members’ work, provide technical guidance, and collaborate with internal stakeholders to deliver reliable enterprise applications.

Designs and deploys scalable AI and machine learning systems using Python and TensorFlow. Responsibilities include data wrangling, complex analysis, NLP, deep learning, data pipeline management, data integration, and model optimization. The role also involves stakeholder collaboration, aligning AI initiatives with business goals, mentoring junior team members, and contributing to data infrastructure and engineering practices.

Supports client data and analytics engagements by designing validation approaches, building data integration and transformation solutions, analyzing data quality issues, testing pipelines with SQL, documenting findings, and recommending corrective actions. The role collaborates with clients, manages workstreams, mentors junior team members, and applies Agile methods while delivering risk and regulatory data solutions.

Participate in an 11-week commercial lines underwriting internship evaluating business operations, assessing risk, developing insurance solutions, and supporting business decisions. Gain exposure to commercial insurance products, risk assessment, relationship management, and customer needs while completing meaningful projects and professional development activities. Collaborate with experienced underwriters and build analytical, communication, negotiation, and decision-making skills.

Leads logistics analytics and systems projects across transportation, warehousing, inventory, and integrated supply chain operations. Translates operational problems into process, data, and technology solutions; develops SQL analyses, Tableau dashboards, and Python automation; and improves KPI visibility, cost, productivity, service, and data integrity. Coordinates requirements, testing, training, change management, stakeholder communication, and benefits tracking across Logistics, IT, Finance, and external providers.

Leads the architecture, technical delivery, integrations, data foundation, reliability, compliance, and continuous improvement of Coupa’s revenue systems stack. Establishes platform standards, roadmaps, automation and AI capabilities, change controls, and incident management practices. Partners with IT, Information Security, Procurement, Finance, and vendors; evaluates and consolidates platforms; and oversees technical delivery across Salesforce and other go-to-market systems.

Manage implementation and launch of new skilled nursing facility accounts, including kickoff meetings, stakeholder communication, timelines, compliance, and 30-, 60-, and 90-day follow-ups. Re-engage existing facilities, address objections, support membership and penetration goals, collaborate with sales and account teams, provide reporting insights, and build trusted partner relationships. The role requires health insurance licensing, extensive travel, occasional evenings and weekends, and strong project management, negotiation, and communication skills.

Leads eight enterprise and strategic sales executives selling Moveworks solutions to manufacturing accounts across the United States. Responsibilities include territory and quota planning, sales strategy, pipeline and forecast management, opportunity development, C-level engagement, recruiting, coaching, performance management, and cross-functional collaboration. The role requires consistent quota achievement, enterprise software sales leadership, strategic relationship building, financial and analytical acumen, and willingness to travel more than 50%.

Drives HPE private cloud AI sales across a multi-state territory, creating pipeline, developing net-new business, engaging executives, and closing complex enterprise opportunities. Advises customers on generative AI, infrastructure, hybrid cloud architectures, economics, security, and governance. Coordinates account managers, architects, services, partners, and executives through discovery, validation, business-case development, negotiation, and close while serving as an AI sales subject-matter expert.

Ten-week sales internship supporting field sales and account management teams. Responsibilities include learning employee benefits products, developing broker and client relationship skills, using Salesforce, BenefitFlow, Tableau, and generative AI tools, collaborating cross-functionally, participating in professional development, and completing a capstone project. The intern will gain practical experience in business development, sales support, analytics, and client-facing business operations.

Build and operate foundational developer infrastructure across CI, build systems, deployment orchestration, and test platforms. Improve build speed, deployment safety, test reliability, observability, and engineering productivity at scale. Own services from architecture through production, including SLOs and on-call operations. Lead cross-functional technical projects, partner with engineering teams, mentor engineers, and shape platform strategy.

Senior Designer responsible for developing high-impact brand and marketing creative across event branding, environmental design, presentations, campaigns, and production assets. The role involves driving projects from brief to delivery, collaborating cross-functionally, maintaining design systems and brand guidelines, using data to inform decisions, and applying AI tools to accelerate creative exploration and production.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.