Top Artificial Intelligence Jobs

Develop and optimize Oracle Fusion Data Intelligence analytics, reporting, semantic models, data integrations, and augmentation solutions. The role supports Oracle ERP, HCM, and SCM data, including OTBI, BI Publisher, ODI, ETL, SQL, and PL/SQL development. Responsibilities include requirements gathering, data cleansing and validation, cross-functional collaboration, and contributing to an ERP analytics roadmap. This is an onsite role in Des Moines, Las Vegas, or Portland, with an initial 3–4 month W2 engagement.

Drive pipeline and manage the full sales cycle for V7 Go, an AI platform serving insurance organizations. Build tailored business cases, develop multiple champions across technical and commercial stakeholders, and close $30,000–$250,000 ARR deals. Serve as an insurance-industry AI expert and strategic advisor while partnering with marketing, sales development, account management, and solution engineering teams.

Own inbound and outbound sales for a real estate lead marketplace. Conduct discovery calls and demos, qualify customer needs, close new business, develop existing accounts, generate pipeline, maintain CRM records, follow up consistently, and achieve revenue targets. The role is remote, works US hours, and offers uncapped commission with potential advancement into sales management.

Design, develop, and maintain scalable backend systems for a composite AI platform (agent-based systems, LLM integrations, RAG). Own technical vision and roadmap, make architecture decisions, establish engineering best practices, provide senior technical leadership, and deliver high-impact production software.

Own customer deployments from contract through go-live and ongoing adoption. Lead discovery, data mapping, migration, configuration, workflow design, integration troubleshooting, and implementation timelines across ERP, PLM, and MES systems. Use SQL and GraphQL to validate data and resolve sync issues, support executive stakeholders, identify expansion and adoption risks, and translate recurring customer problems into product requirements. Build deployment playbooks, documentation, onboarding runbooks, and success metrics while traveling frequently to customer sites.

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.

Work directly with the CEO as a Chief of Staff MBA intern: build operations and meeting cadences, manage projects and dashboards, plan events, conduct market and competitive research, drive cross-functional strategic initiatives, and influence product design and roadmap decisions. In-office five days a week with long hours; hands-on startup experience expected.

Build and own large-scale backend and full-stack systems supporting AI agents, data integrations, sync engines, and construction financial products. Design major subsystems, make architecture and build-versus-buy decisions, debug complex production issues, improve scalability and performance, and mentor engineers. Work across cloud infrastructure, distributed systems, legacy on-premise integrations, caching, data consistency, and AI-powered workflows while collaborating directly with founders and customers.

Perform outbound prospecting (email, calls, social) to generate qualified healthcare leads, research targets, craft personalized messaging, qualify prospects, maintain CRM records, book meetings, and collaborate with the founder to optimize outreach and meet weekly/monthly performance goals.

Build Kastle’s growth engine by mapping target accounts, developing outbound campaigns, creating automated growth tools, owning product messaging, managing events, and testing creative ways to reach senior buyers. The role combines writing, campaign execution, data analysis, AI-enabled automation, lead tracking, sales enablement, and continuous experimentation to generate qualified sales opportunities across financial-services markets.