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

Reviews AI-generated legal deposition transcripts against audio or video, correcting grammar, punctuation, formatting, terminology, speaker identification, and completeness. Conducts legal terminology research, applies transcription style guidelines, performs live data tagging, and meets deadlines while adapting to evolving AI transcription tools and workflows.

Designs, installs, programs, validates, and supports six-axis robotic automation solutions at customer sites. Partners with sales, customers, and engineering teams to develop applications, create technical enablement materials, test integrations, and contribute to marketing collateral. Requires hands-on mechanical, electrical, and software experience in manufacturing, automotive, or industrial automation environments, with extensive domestic travel and factory-floor work.

Leads NOVO’s delivery operating system across service desk, project delivery, onboarding, resource planning, reporting, and service quality. Establishes scalable processes, governance, KPIs, dashboards, capacity planning, escalation management, and continuous improvement practices. Coordinates cross-functional teams, improves customer experience and delivery predictability, manages operational systems, and champions automation and AI adoption. Oversees budgeting, resource optimization, team leadership, and operational accountability in a managed technology services environment.

Own FAR.AI’s internal IT and security function, including accounts, devices, identity and access management, onboarding, offboarding, office networking, support, endpoint hardening, data protection, governance, and vendor risk. The role will remediate security gaps using threat modeling, automate self-service infrastructure, partner across teams, communicate and manage change, and hire and lead an IT Coordinator.

Administer and extend CRM, contact center, and AI-agent platforms supporting Customer Operations. Configure workflows, routing, permissions, prompts, knowledge sources, integrations, and automations. Troubleshoot data-flow issues, monitor AI performance, document system configurations, maintain runbooks, train users, evaluate tools, and translate business requirements into reliable system configurations.

Build and operate CrewAI’s cloud and enterprise infrastructure across AWS, Azure, and GCP. Develop CI/CD pipelines, deployment automation, observability, security controls, self-hosted installation tooling, and reliability processes. Support containers, Kubernetes, databases, queues, networking, secrets, and production workloads. Participate in incident response and on-call operations while partnering with runtime and product engineering teams to improve deployment safety, scalability, and customer production environments.

Manage a customer book of business across onboarding, adoption, expansion, retention, and renewals. Build success plans, lead executive business reviews, provide data-driven e-commerce insights, and collaborate with sales and internal teams. The role focuses on customer satisfaction, revenue growth, lifecycle management, and trusted-advisor relationships with users and executives.

Own renewals and expansion for an SMB customer portfolio, managing high-volume transactional sales cycles. Responsibilities include forecasting, negotiating, closing renewals, identifying usage-driven upsell and cross-sell opportunities, monitoring consumption data, preventing churn, engaging decision-makers, and partnering with Customer Success, Solutions Engineering, Product, and Support. The role requires selling a technical AI product to engineering and data science buyers while communicating customer patterns internally.

Design, develop, test, and optimize safe, scalable real-time software for production autonomous vehicle systems. Architect continuous learning infrastructure for ML model deployment and monitoring, analyze algorithms, and collaborate with embedded, platform, AI, sensor, and compute teams. Support perception, prediction, and planning integration while contributing to highway and urban autonomous driving capabilities.

Own end-to-end AI product development for enterprise clients, from requirements and rapid LLM prototyping through production deployment. Responsibilities include data modeling, ETL pipelines, integrations, evaluation, observability, security, reliability, cost management, and client communication. The role requires shipping real AI products, iterating based on usage, and independently managing ambiguous technical and product decisions.