Top Artificial Intelligence Jobs in Raleigh-Durham, NC

Build, maintain, and improve production AI services for document understanding including LLM pipelines, background jobs, databases, and internal tools. Implement features, debug production issues, write tests, and contribute to evaluation frameworks to improve model quality and system reliability. Collaborate with a small engineering team and take increasing ownership over platform components.

Design, develop, customize and maintain enterprise Sitecore solutions (versions 9/10, SXA, JSS, XM Cloud). Produce technical specs, implement components, test and debug in test and production, support teammates, perform demos to customers, and escalate/resolve issues.

Build and own the technical roadmap: design AI-first interfaces and APIs, architect scalable ETL pipelines, develop data models for ML features, ship autonomous B2B workflows (PO generation, vendor sync, schedule optimizations), and establish engineering standards, CI/CD, and mentoring.

Own post-sales relationships for Fortune 500 clients, lead enterprise-scale implementations and HRIS/ATS integrations, develop executive success plans, train client teams, analyze and present ROI/KPIs, drive adoption and upsells, and represent customer needs to Product and engineering to ensure compliance and strategic impact.

Lead and scale marketing across consultancy and product studio: define positioning, run digital/social/content campaigns, implement lead-gen systems, manage internal and external teams, integrate AI and martech, track KPIs and ROI, and evolve brand voice and messaging.

Support the sales team by managing client relationships, meeting with clients online to assess needs, following up on leads, reaching out to prospects, and maintaining client data in a CRM to ensure satisfaction and growth.

Build and maintain client relationships, identify new business opportunities, develop sales strategies, present value propositions, negotiate contracts, close agreements, and drive revenue growth while monitoring market and competitive trends.

Join a remote engineering team to write, test, and maintain code under senior guidance; participate in code reviews, standups, and sprint planning; debug and resolve application issues; and continuously learn new technologies and best practices.

Own the full lifecycle of production classification and detection models, including transformer fine-tuning, entity detection, behavioral risk scoring, training, serving, versioning, evaluation, drift detection, and retraining. Build SageMaker-based ML systems and define output contracts supporting audit and policy enforcement. Lead the evaluation harness and mentor a co-op while operating as the company’s sole ML engineer.

Lead the full product lifecycle for verifiable computing solutions focused on AI and data integrity. Define product vision, roadmap, go-to-market strategy, branding, and positioning; lead cross-functional teams; develop strategic partnerships with technology and data platform companies; oversee product content; and monitor trends in AI governance, cybersecurity, and computational integrity.