Top Artificial Intelligence Jobs in Oklahoma City, OK

Own enterprise sales across large K-12 school districts, driving territory strategy, self-sourced pipeline, stakeholder consensus, complex 6–18 month sales cycles, and net-new logo acquisition. Manage pilots, RFPs, board approvals, budgets, forecasting, and deal-team orchestration. The role requires selling six-figure contracts, achieving a $1M+ quota, understanding education funding, and traveling more than 50% of the time.

Designs and develops APIs, system integrations, and AI-agent workflows for enterprise applications. Builds integrations with platforms such as Salesforce and REST APIs, deploys and supports solutions on AWS, and develops AI-powered automation using LLMs, tool calling, and multi-step workflows. The role includes client requirements gathering, troubleshooting, reliability optimization, cross-functional collaboration, and mentoring junior developers.

Lead technical architecture for strategic AI/HPC compute infrastructure opportunities, including GPU cluster design, benchmarking, orchestration, virtualization, and compute-to-network integration. Partner with sales and solutions teams through complex pre-sales cycles, engage executive stakeholders, guide proofs of concept, provide product feedback, publish technical guidance, mentor technical staff, and represent the company at industry events. Travel approximately 10% domestically and internationally.

Facilitate adaptive, hands-on AI workshops for startups, scale-ups, and SMBs; teach AI tools, workflows, adoption mindsets, and behavioral change. Maintain fluency across Claude, Gemini, and ChatGPT, develop learning content, support client relationships, contribute to marketing and thought leadership, and help improve Clarinet’s workshop offerings based on participant feedback.

Own end-to-end development of AI-native healthcare solutions, from exploratory data analysis and model strategy through production deployment and monitoring. Fine-tune multimodal generative models, orchestrate AI agents, define rigorous evaluations, build scalable backend systems, and monitor data drift and model performance. The role requires strong software architecture, cloud infrastructure knowledge, observability, testing, autonomous execution, and technical mentorship in a high-stakes healthcare environment.

Build and maintain full-stack software for startup clients, including backend services, frontend experiences, new features, redesigns, bug fixes, and product improvements. Collaborate daily with product managers, designers, and engineers in a distributed, agile environment. Take ownership across the technology stack, write clean maintainable code, contribute to client missions, and support team growth and knowledge sharing.

Develop practical AI solutions for enterprise customers by translating business needs into solution plans, prototypes, workflows, evaluations, and production implementations. Guide trade-offs involving reliability, scalability, governance, and customer impact; coordinate stakeholders, resolve delivery risks, measure adoption and value, and convert recurring implementation lessons into reusable capabilities.

Build and deploy production AI agents for real customers. Responsibilities include orchestrating LLM pipelines, integrating APIs and tools, developing React interfaces, implementing RAG and document-processing systems, deploying serverless applications, and monitoring performance. The role requires strong Python or JavaScript skills, hands-on OpenAI and multimodal LLM experience, vector databases, agent frameworks, function calling, and full-stack integration. Applicants must be pursuing a Master's or PhD in a technical field.

Develop and maintain infrastructure for rapid software prototyping and deployment across cloud, private cloud, and bare-metal environments. Manage servers and Kubernetes clusters, configure GPU systems for large language models, optimize performance, build monitoring and alerting, and advise on localized data-center deployments. The role also requires software engineering, Linux administration, security awareness, automation, and collaboration across international teams.

Manage day-to-day operations of four owned data centers and a global InfraOps team. Own capacity planning, hardware lifecycle, vendor/budget management, incident response, and runbook/alert hygiene. Oversee core stack (Linux fleet, FreeIPA, Ansible/Salt, MAAS, Zabbix), spine-leaf networking, and stateful data tiers (Aerospike/Kafka/ClickHouse/HDFS) under strict low-latency SLAs. Partner with security/compliance and run cloud-vs-colo evaluations.