Artificial Intelligence Jobs in Irving, TX

Validate and challenge in-house and third-party NLP, generative, and agentic AI models: review data and sampling, develop test models and reusable validation code, assess model performance and monitoring, write analytical reports, coach junior staff, and communicate with stakeholders, regulators, and auditors to ensure compliance with MRM governance.

Design, deploy, and operationalize enterprise AI/LLM applications (RAG, agents, vector DBs) to detect and mitigate emerging risks. Build prompt frameworks, dashboards, APIs, and governance controls; lead cross-functional initiatives and advise executives on AI-driven risk analytics.

Lead AI governance and risk for product initiatives by coordinating across AI Product, COEs, Legal, Risk, Compliance, Audit, and Technology. Establish governance structures, operating rhythms, metrics, and processes to operationalize model oversight, reduce risk, and accelerate responsible AI adoption. Support audit, remediation, and cross-functional decision making while improving delivery speed and stakeholder experience.

Lead design and deployment of agentic AI solutions across the enterprise. Create architecture deliverables, design orchestration and data retrieval patterns, evaluate emerging AI frameworks, partner with IT and product teams, and ensure scalable, production-ready AI infrastructure and MLOps practices.

Design, develop, validate, operationalize, and maintain large-scale data models and analytics. Perform end-to-end analytics including data wrangling, feature engineering, modeling (including NLP and ML), MLOps, and stakeholder communication to drive business insights and improve operational efficiency.

Lead and grow a team of Azure Solution Engineers to drive cloud migration, application modernization, and AI adoption for Education, Nonprofit, and IGO customers. Partner with sales, engineering, product, and partners to deliver secure, governed, and scalable Cloud & AI solutions, scale repeatable plays, and coach technical talent to achieve measurable customer and business outcomes.

Lead enterprise Employee Relations strategy and team; advise executives and HR partners on complex ER matters; oversee investigations, workforce transitions, policies, compliance, ER technology, analytics, and leader education to mitigate risk and improve outcomes.

Design, build, and maintain scalable cloud-native data pipelines, microservices, and platforms to support real-time and batch processing. Collaborate with architects and stakeholders to translate requirements, implement AWS-based ingestion/streaming solutions, enforce data quality/testing, and operate observability and CI/CD practices to ensure reliable production data systems for autonomy initiatives.

Lead design, build, and operate scalable data pipelines, microservices, and cloud-native data platforms. Collaborate with architects and stakeholders to translate requirements, ensure data quality and testing, implement streaming and batch solutions on AWS, and maintain operational excellence, monitoring, and CI/CD for high-availability data systems supporting autonomy initiatives.

Responsible for building conversational AI experiences using Dialogflow CX, integrating backend systems, conducting QA, and leading teams on AI initiatives.

The Cyber AI Senior Specialty Software Engineer will design, develop, and deploy AI applications while integrating them with existing systems and resolving technical issues.

Provide legal support to the General Counsel across commercial transactions, technology and IP licensing, SaaS/API/data agreements, BAAs and HIPAA compliance, contract negotiation, subpoena responses, investigations, and cross-functional counseling to minimize legal risk and support product and business objectives.

Lead a new AI & Process Transformation function within Information Security Services to redesign operating models, prioritize and deliver automation and AI initiatives, drive process modernization from assessment through benefits realization, build business cases and roadmaps, and lead change adoption across senior stakeholders to improve efficiency, scalability, and organizational effectiveness.

Develop, analyze, and implement application systems using Python and generative AI frameworks. Build and maintain RESTful APIs, cloud-deployed containerized services, and ensure security, testing, and operational support. Consult with stakeholders, perform feasibility and post-implementation analysis, mentor junior analysts, and drive compliance with policies and risk controls.

Lead strategy and delivery of digital workplace infrastructure products to improve employee experience. Use DEM/DEX telemetry and analytics to prioritize backlogs, define requirements, and drive automation, self-service, and operational efficiency. Partner with engineering, operations, and support to monitor KPIs, resolve issues, and continuously improve product outcomes using agile practices.

Design, build, and deploy scalable AI and machine learning solutions, leading full AI lifecycle, collaborating with teams, and ensuring systems align with client needs.

Lead AI Quality Engineering initiatives for enterprise AI, establishing AI-native testing, validation, runtime quality controls, observability, and automation. Coordinate cross-functional validation, release readiness, and production reliability for LLM-enabled workflows and AI platforms. Mentor teams and drive adoption of AI-assisted testing, telemetry analysis, and continuous improvement across healthcare-related AI solutions.

Design, build, optimize, and deploy agentic AI/LLM solutions and inference pipelines for consumer platforms. Integrate AI agent frameworks with customer success and retail systems, collaborate on production roadmaps, perform red-teaming and testing, optimize APIs and data integrations for scale and performance, prototype emerging frameworks, and document technical specifications and pilot results.

Lead individual contributor building, deploying, and monitoring complex propensity and churn models. Manage end-to-end ML pipelines, enable microsegmentation and personalization, mentor engineers, and present model insights to senior stakeholders to drive retention and business impact.

Maintain and improve production AI systems by building real-time monitoring, drift detection, safety guardrails, fallback systems, and automated CI/CD retraining pipelines. Diagnose live-model incidents, ship hotfixes, and collaborate with platform and data science teams to scale secure, ethical ML operations across cloud, on-prem, and edge environments.

Lead a team of propensity modelers, deploy data scientists into cross-functional pods, partner with marketing to reduce churn via ML-driven personalization, manage chapter operations (hiring, training, resources), establish modeling governance and standards, drive cross-functional collaboration, and present AI strategies to executives.

Lead AI transformation and technical pre-sales for Finance & Supply Chain ERP, driving POCs, workshops, demos, and technical win strategies. Engage C-suite and technical decision makers, collaborate with partners and engineering, address Copilot/AI Agents compliance and security concerns, and support pipeline creation, deal velocity, and competitive wins for D365 F&SC and Microsoft AI solutions.

Lead the development of an intelligent document processing platform using Generative AI, managing a high-performing engineering team, and driving technical innovation.

Lead AI FinOps for enterprise AI platforms by managing cloud AI spend, optimizing token/GPU/inference costs, building forecasting and chargeback models, defining governance and financial guardrails, partnering with cross-functional teams, and delivering executive reporting to drive cost-effective, responsible AI adoption.

Lead technical design and delivery of enterprise-scale LLM and agentic AI systems for banking. Architect, implement, and deploy production AI solutions, integrate multiple LLM providers, define evaluation metrics, drive rapid MVP delivery, mentor engineering teams, and align AI platforms with business and risk objectives.