Artificial Intelligence Jobs in Frisco, TX

Owns the enterprise AI portfolio, product lifecycle, integrated roadmap, operating cadence, and cross-team delivery dependencies. Leads planning, portfolio reviews, executive forums, backlog management, prioritization, Agile ceremonies, risk resolution, and high-visibility initiatives. Partners with engineering, architecture, security, identity, and leadership teams to deliver AI products aligned with business goals, technical performance targets, employee satisfaction, and committed timelines.

Leads technology and risk-based internal audits across cybersecurity, engineering, network, privacy, and business functions. Owns audit planning, scoping, testing, reporting, issue validation, remediation tracking, budgets, and timelines. Oversees external co-source audit partners, develops audit staff, contributes to risk assessments and annual audit planning, and communicates findings to management. Applies data analytics, AI, and machine learning to improve audit procedures and identifies actionable control and risk insights.

Conduct operational, financial, and compliance audits; assess risks and internal controls; develop audit programs and test plans; analyze data; document workpapers; identify control gaps; and communicate findings and recommendations. Collaborate with business partners and audit teams while exploring data analytics, AI, and automation to improve audit effectiveness.

Leads complex internal audits and advisory engagements across operational, financial, compliance, and business functions. Plans audit scopes, assesses risks and controls, supervises audit teams and co-source partners, reviews evidence and workpapers, develops findings and recommendations, and oversees remediation. Builds stakeholder relationships and communicates business risks to management. Advances audit methodologies through data analytics, AI, machine learning, and automation while supporting annual planning, resource management, and strategic initiatives.

Leads pricing operations across North America and Latin American regions, overseeing pricing strategy, complex deal modeling, financial analysis, process modernization, CPQ integration, governance, and operational excellence. Builds and manages a high-performing team, partners with sales, finance, product management, and executive stakeholders, and drives automation, efficiency, SLA performance, and scalable pricing processes.

Own the end-to-end enterprise AI training and adoption product lifecycle, including strategy, roadmap, training content, vendor coordination, product releases, and the AI Champion Network. Partner with technical teams, business leaders, vendors, and subject matter experts to drive safe AI adoption. Analyze usage, completion, and employee feedback data to prioritize improvements and measure outcomes across a distributed workforce.

Supports Public Storage’s investor relations program through financial analysis, modeling, investor presentations, earnings communications, peer and sell-side analysis, shareholder outreach, and strategic initiatives. Partners with executives, investors, analysts, and cross-functional teams on corporate strategy, capital markets, acquisitions, ESG, and performance analysis.

Own the enterprise AI assistant product lifecycle, including vision, strategy, roadmap, capability onboarding, entry points, backlog, and production performance. Evaluate AI advancements, conduct research, define requirements, coordinate Agile delivery, manage quality and usage-based costs, and partner with security, privacy, governance, platform, business, and operations teams. Success is measured through routing accuracy, answer quality, cost per interaction, product performance, and employee satisfaction.

Own the Responsible AI evaluation framework, evaluation program, and AI transparency standard. Define product vision, strategy, roadmap, features, user stories, and backlogs for AI evaluation tests and benchmarks. Partner with Legal, Privacy, AI engineering, and business stakeholders to prioritize evaluations, coordinate releases, monitor quality, and close findings. The role requires technical experience, product management expertise, Agile SDLC knowledge, and familiarity with Responsible AI frameworks and regulated AI applications.

Leads customer implementations of ONESOURCE Direct Tax solutions, including solution design, project delivery, best-practice reviews, remediation, proofs of concept, and automation. Partners with Product, Sales, and Customer teams, manages multiple engagements, identifies expansion opportunities, advises clients, and builds AI-powered tools using Power Automate and related technologies. Requires deep hands-on tax technology expertise, advanced automation capabilities, and strong customer communication skills.

Technology interns participate in a 12-week, in-person program in Louisville, supporting projects across software and cloud engineering, data analytics, AI, cybersecurity, UX, agile development, and project management. Interns collaborate with experienced technologists, contribute to business and healthcare technology initiatives, attend professional development activities, and gain exposure to executive presentations and technical teams.

Own the SafeSend product portfolio and lead its evolution into an AI-driven Gather & Deliver experience. Responsibilities include converging SafeSend and TaxCaddy, developing reusable workflow components, expanding APIs and integrations, enabling agent orchestration through CoCounsel, and delivering reliable tax-season performance. The role requires platform product leadership, customer migration expertise, AI product fluency, systems thinking, stakeholder management, and team-building skills.

Leads complex AI transformation engagements for legal, tax, and trade clients, from discovery and workflow redesign through adoption and value realization. Advises executives, shapes commercial opportunities, establishes measurement frameworks, collaborates with AI engineers and product teams, resolves complex delivery decisions, and develops reusable consulting methods and value frameworks.

Leads AI transformation consulting engagements for legal, tax, and trade teams using CoCounsel. Responsibilities include workflow discovery, current- and future-state design, adoption planning, stakeholder workshops, evidence-based measurement, responsible-use controls, risk mitigation, and collaboration with AI engineers and product teams to deliver measurable client outcomes.

Serves as the liaison between the business unit and AI Center of Excellence. Manages AI use-case intake, prioritization, governance, compliance, vendor and platform evaluations, proof-of-concept pilots, and financial stewardship. Translates business needs and technical AI capabilities, maintains model inventories, supports responsible AI and risk assessments, and drives adoption through enablement, training, change management, and AI literacy initiatives.

Owns T-Mobile’s enterprise AI enablement product, including the roadmap, backlog, curriculum, learning paths, rollout communications, and champion network. The role improves employee adoption of GenAI tools and agents by creating technical and non-technical learning experiences, measuring usage and effectiveness, gathering feedback, and continuously refining content. It partners with HR Learning and Development while managing AI-specific enablement strategy and delivery.

Design, build, and deploy production-grade LLM agents, RAG systems, voice/image AI, and automation workflows. Implement TTS/STT and generative image models, develop full-stack APIs/microservices, optimize performance, and ensure security/compliance while collaborating with product and operations teams.

Design, build, and maintain batch and streaming data pipelines on GCP (BigQuery, dbt, Airflow, Pub/Sub). Productionize ML workflows (training, inference, CI/CD) using Cloud Run, GKE, and Vertex AI. Support real-time inference, RAG/LLM assistants, graph-based recommendations, and model monitoring. Collaborate with cross-functional teams to deliver scalable, reliable data products and observability for downstream ML and analytics.

Leads a global AI engineering organization, owning multi-year strategy, product alignment, team transformation, vendor governance, and engineering operations. Oversees production AI lifecycle delivery, including retrieval, model integration, evaluation, deployment, monitoring, reliability, security, CI/CD, and AWS infrastructure. Establishes data-driven engineering metrics, AI adoption guardrails, cost controls, and responsible AI practices while partnering with product and technology leaders to deliver strategic initiatives.

Lead and manage a team building scalable full-stack legal research products, AI agents, retrieval-augmented generation systems, APIs, and cloud-native services. Provide hands-on technical leadership across architecture, coding, DevOps, security, reliability, and AI-assisted development. Hire, coach, and develop senior engineers while partnering with Product, Design, and stakeholders to deliver production-grade solutions on AWS.

Architects and ships production AI agent systems, including multi-component pipelines, tool integrations, orchestration infrastructure, observability, evaluations, and reliability practices. The role owns complex systems end-to-end, contributes to technical architecture and progressive delivery, collaborates across product and engineering, and mentors engineers. It requires strong backend, distributed systems, cloud infrastructure, LLM, and agentic development experience.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Designs and leads enterprise AI systems for legal research, including RAG pipelines, knowledge graphs, autonomous agents, and AI platforms. Provides technical strategy, architecture, mentoring, governance, testing, observability, and operational leadership. Partners with research, engineering, design, and product teams to launch scalable, secure AI products. Requires hands-on software engineering expertise in generative AI, cloud-native systems, APIs, distributed systems, and production AI deployments.

Own high-visibility AI transformation programs from strategy through delivery. Responsibilities include structuring ambiguous challenges, developing program plans, managing scope, budgets, risks, dependencies, and benefits, analyzing data and building business cases, maintaining PMO governance, leading cross-functional teams, and influencing senior stakeholders through steering committees and executive reporting.

Leads AI specialty sales and partnership teams serving small law firms. Owns go-to-market strategy, revenue growth, customer acquisition, adoption, pipeline, and market share for CoCounsel Legal and related AI solutions. Builds high-performing sales teams, develops co-sell and partner ecosystems, coordinates cross-functional execution, advances sales enablement, and represents Thomson Reuters as an AI thought leader in the legal technology market.