Top Artificial Intelligence Jobs in Oklahoma City, OK

Leads the vision, strategy, organizational development, and business performance of DEUNA’s agentic AI product organization. Oversees Product Managers, defines scalable AI agent orchestration capabilities, partners with engineering on platform architecture, and drives automation, evaluation, monitoring, safety, compliance, and enterprise adoption. The role also aligns product initiatives with growth, revenue, merchant needs, and market expansion.

Own the vision, strategy, and roadmap for Archy Revenue, an AI-powered dental revenue-cycle product. Drive claims, payment, reconciliation, automation, adoption, upsell growth, pricing, and packaging. Partner with engineering, design, sales, customer success, and marketing to deliver trusted AI workflows, meet HIPAA and security requirements, establish product analytics, and translate customer needs into impactful product improvements.

Own cloud infrastructure, EKS, AWS systems, CI/CD pipelines, preview environments, observability, security, and compliance. Build developer tooling and internal applications, while leading AI adoption across Engineering through agent workflows and custom solutions. Support product analytics and data science pipelines, collaborate closely with internal stakeholders, and maintain platform reliability end to end.

Work on front-end and back-end web projects: create and redesign websites, build sitemaps and wireframes, collaborate with teams, and focus on UI/UX and performant back-end functionality.

Lead Factory’s developer relations strategy across technical content, community, events, partnerships, and social channels. Build tutorials, demos, documentation, sample applications, and case studies; represent Factory publicly; grow developer communities; develop ecosystem partnerships; gather product feedback; and measure developer adoption, engagement, and retention. The role requires strong technical credibility, familiarity with AI-powered development, exceptional communication skills, and close collaboration with Product and Engineering.

Own end-to-end technical onboarding for healthcare SaaS customers, including EMR integration, workflow configuration, data validation, troubleshooting, and go-live delivery. Serve as the primary technical contact for customer IT stakeholders, collaborate with Product, R&D, Medical, and Customer Success teams, and improve scalability through automation, runbooks, and implementation frameworks.

Own the full enterprise sales cycle across the Mountain and Southwest territories. Build pipeline, develop account plans, engage CISOs and executive buyers, lead technical evaluations, create business cases, negotiate complex agreements, close new and expansion business, and maintain accurate forecasts. The role requires strong cybersecurity expertise, established enterprise security relationships, quota-carrying sales experience, technical credibility in security, cloud, and AI, and willingness to travel.

Build and maintain finance data pipelines, warehouse models, dashboards, and automations for unit economics, technology budgeting, burn, runway, margins, deal desk, and sales compensation. Develop internal tools and LLM-based agents that help non-engineers access trusted financial data. Partner with finance, sales, and engineering leadership to reconcile discrepancies and improve revenue, cost, billing, payroll, cloud-spend, and accounting workflows.

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.

Conduct research on frontier AI systems and develop datasets, experiments, prototypes, tooling, evaluation frameworks, and reinforcement learning environments. Investigate synthetic and agentic data generation, post-training, model understanding, benchmarks, and evaluation. Collaborate with research, engineering, product, and operations teams to translate findings into scalable AI applications, while contributing to technical publications, open-source work, mentorship, and the broader AI research community.