Top Entry Level Artificial Intelligence Jobs in Dallas-Fort Worth, TX

Manage approximately 30 enterprise SaaS accounts across onboarding, adoption, renewals, and expansion. Lead kickoffs, success planning, QBRs, health reviews, enablement, and ROI discussions. Identify risks, resolve technical and business blockers, and coordinate with Sales, Support, Solutions Engineering, Product, and Engineering. Provide customer feedback, improve scalable success programs, and drive retention, adoption, and revenue growth.

Own expansion revenue across existing dealership accounts by selling additional products and expanding into more locations within dealer groups. Responsibilities include building account relationships, identifying growth opportunities, running demos, creating proposals, negotiating and closing deals, partnering with customer success, and sharing customer feedback. The role requires quota-carrying sales or account management experience, a record of achieving expansion or upsell targets, and experience selling to automotive dealerships.

Build and maintain evergreen technical talent pipelines for data engineering, machine learning, and full-stack roles. Source and engage candidates, coordinate with sales, delivery, engineering, and hiring leaders, define technical assessments, manage full-cycle recruiting, optimize sourcing and conversion metrics, and maintain candidate readiness for rapid deployment. This is a 3–6 month contract engagement at approximately 40 hours per week.

Supports customers through ticket triage, emergency phone support, technical guidance, and best-practice consultation. Processes customer materials through glossary development tools, validates glossaries using human and machine testing, and assists with customer success workflows, tracking, reporting, and sales data requests. The role is fully remote and focused on helping clients deliver accurate real-time translation events.

Own federal and B2B business development for cybersecurity products and managed services. Identify and qualify government opportunities, build relationships with agencies and Federal System Integrators, shape requirements, develop partnerships, manage pipeline, and support capture and proposal activities. Use knowledge of FedRAMP, ATO/RMF, FISMA, GRC, and federal acquisition processes to position solutions across FedCiv and DoD/IC markets.

Owns commercial relationships with current and prospective enterprise healthcare accounts in the Northeast. Drives renewals, expansions, new use cases, revenue growth, and long-term account strategies. Leads consultative sales motions, executive stakeholder relationships, account planning, and ROI-based positioning. Coordinates Customer Success, Solutions, Product, and Delivery teams while prospecting for new opportunities and providing market insights. Requires healthcare expertise, enterprise account management, value-based selling, executive communication, PowerPoint proficiency, data analysis, and up to 50% travel.

Own Spellbook’s social media function, including strategy, content calendar, publishing, community engagement, executive ghostwriting, brand voice, and performance measurement. The role will build the company’s social presence from scratch, grow organic reach and engagement, develop relationships with legal tech audiences and influencers, and use analytics and platform trends to improve results.

Own enterprise and strategic SaaS accounts by identifying new opportunities, managing complex sales cycles, conducting POCs, negotiating bespoke agreements, closing high-value deals, and driving adoption and expansion. The role includes territory planning, prospecting, stakeholder engagement, forecasting, tailored demos and business cases, pipeline optimization, and coaching team members while contributing to go-to-market improvements.

The Content & Prompt Operations Specialist manages AI-assisted content workflows, ensuring accuracy and engagement in content produced. Responsibilities include writing prompts, drafting content, proofreading, and improving AI outputs while following structured processes.

Build and deploy generative AI applications and multi-agent systems on Google Cloud using Vertex AI, Python, BigQuery, RAG, and secure enterprise data integrations. Develop data pipelines, train and serve models, evaluate AI output, protect sensitive information, troubleshoot production systems, and collaborate with technical and business stakeholders.