Artificial Intelligence Jobs in Irving, TX

Leads the design, development, operation, and governance of enterprise API, AI, and cloud-native platforms. Responsibilities include managing API gateways, developing API proxies and GraphQL services, building Terraform-based infrastructure automation, implementing CI/CD and self-service deployment, enforcing security controls, designing multi-cloud networking, and providing technical leadership, mentorship, and incident management.

Lead the design and development of scalable data pipelines, microservices, cloud-native ingestion systems, and streaming solutions. Collaborate with architects, engineers, product teams, and business stakeholders to build reliable data platforms using Python, Java, AWS services, SQL, and relational and NoSQL databases. Establish data quality, testing, monitoring, automation, and validation frameworks while optimizing performance and resolving production issues across distributed systems.

Leads product strategy, customer research, competitive intelligence, and partner engagement for Citi’s U.S. Consumer Cards digital and client experience organization. Shapes digital and CX roadmaps, evaluates emerging technologies including AI, guides investment decisions, aligns senior stakeholders across business and functional teams, oversees executive governance, and develops strategic recommendations. Manages a 15–20-person team and influences product innovation, customer experience, and business growth across a complex matrixed organization.

Defines enterprise architecture and operating standards for AI-ready data products supporting Physical AI, simulation, and machine learning. Establishes data domains, contracts, metadata, quality, lineage, security, lifecycle management, and reusable data objects. Integrates labeling, annotation, curation, evaluation, and feedback processes while aligning business, data engineering, and AI teams. Provides strategic architectural leadership across engineering organizations and develops scalable cloud, on-premise, telemetry, streaming, and edge-to-cloud data platform strategies.

Defines enterprise architecture for streaming, batch, event-driven, analytics, and Physical AI data workloads. Designs ingestion, transformation, storage, governance, observability, security, resilience, and lifecycle-management patterns. Establishes platform guardrails, evaluates emerging technologies, and develops architectural roadmaps. Partners with engineering, cloud, and business teams to support AI and autonomy initiatives across large-scale industrial data ecosystems.

Leads AI and emerging-technology research for supply chain executives. Develops market insights, forecasts trends, assesses AI risks and governance, translates AI capabilities into supply chain outcomes, and advises clients on strategic and financial ROI. Creates research and presentation content, supports sales and conferences, mentors analysts, reviews work, and collaborates across Gartner teams. Requires executive presence, strong research, writing, analytical, communication, and presentation skills, with up to 25% travel.

Lead the architecture and hands-on development of a cloud-native enterprise document management platform using AI, intelligent document processing, generative AI, and enterprise search. Build Java and Spring Boot microservices, IDP workflows, semantic and vector search, RAG capabilities, and Azure/Kubernetes solutions. Provide technical leadership, mentor engineers, conduct architecture reviews, and ensure security, reliability, observability, and production support.

Serve as enterprise strategic advisor on AI and automation by researching market and vendor trends, evaluating emerging capabilities, developing evidence-based adoption recommendations, supporting investment and roadmap planning, and briefing senior leaders. Maintain competitive intelligence, assess risks and governance implications, and collaborate with business, product, and governance stakeholders to align strategy and execution.

Supports IT Application Services initiatives involving business analysis, process improvement, data analytics, AI and automation use cases, testing, technology evaluation, and solution delivery. Interns gather requirements, analyze processes and data, prototype solutions with tools such as Copilot and Power Automate, develop recommendations, collaborate cross-functionally, and present findings to leadership. Assignments may support supply chain, commercial operations, or business functions, with structured mentorship and periodic travel.

Leads Verizon’s AI Connect business development strategy for Global Enterprise, with emphasis on Dark Fiber and AI-enabled connectivity. Responsibilities include managing and developing a high-performing team, cultivating C-suite and enterprise relationships, executing go-to-market strategy, expanding strategic partnerships, driving profitable revenue growth, and aligning cross-functional stakeholders across major industry verticals.

Leads Verizon’s AI Connect sales organization, focusing on Dark Fiber infrastructure and AI-enabled connectivity for hyperscalers, data centers, and AI-focused firms. Responsibilities include executing go-to-market strategy, expanding strategic partnerships, driving profitable revenue growth, managing complex enterprise relationships, and developing high-performing sales teams. The role requires expertise in networking infrastructure, AI transformation, solution selling, executive engagement, alliance management, and cross-functional leadership in matrixed environments.

Architect and build Verizon’s enterprise AI control plane, integrating AI developer platforms with governance hubs. Develop APIs, CI/CD governance pipelines, security and responsible AI guardrails, agent simulation, observability telemetry, IAM, and secure routing for autonomous workflows. Collaborate with platform engineering, DevOps, DataOps, data science, and product teams to operationalize models and agents. The role requires LLM operationalization, cloud architecture, platform engineering, applied ML, Python, Kubernetes, and automated safety testing expertise.

Drive Databricks adoption on Azure by leading architecture reviews, proofs of concept, and production deployments. Advise customers and partners on data, analytics, and AI architectures; resolve technical blockers; promote security, governance, reliability, and operational excellence; create reference architectures and reusable IP; and collaborate across sales, engineering, and partner teams to accelerate cloud consumption and measurable customer outcomes.

Designs and leads AI Quality Engineering for enterprise AI applications, LLMs, intelligent automation, and agentic systems. Responsibilities include building validation and testing frameworks, prompt and workflow testing, runtime quality controls, observability, telemetry, drift detection, reliability support, and release validation. The role collaborates across engineering, security, governance, clinical, data, and product teams to validate healthcare workflows and responsible AI deployments, while mentoring quality engineers and advancing AI-enabled testing practices.

Senior Product Manager responsible for developing and scaling products serving General Counsels, Chief Audit Executives, and compliance and risk teams. The role includes gathering client and market insights, defining product strategy and roadmaps, launching and evaluating offerings, analyzing performance, driving adoption and retention, supporting go-to-market efforts, and collaborating with sales, engineering, research, and other cross-functional teams.

Own and administer content operations platforms, including workflow and digital asset management systems. Define content lifecycle processes, manage platform adoption and user enablement, oversee vendors and licenses, prioritize business requirements, and develop platform roadmaps. Partner with Marketing, Creative, IT, and agencies on integrations and scalable workflows. Implement AI and automation use cases to improve content production efficiency, platform utilization, and marketing execution.

Leads development of high-fidelity digital twins, machine dynamics models, and reduced-order models for autonomous construction equipment. Establishes NVIDIA Newton simulation standards, validates models against real-world data, and enables robotics, autonomy, reinforcement learning, synthetic data, and virtual validation workflows. Collaborates across engineering, AI, controls, hydraulics, and machine systems teams while shaping Caterpillar’s long-term physical AI and simulation strategy.

Leads development of scalable full-stack applications using Java, Angular, microservices, and event-driven architectures. Integrates and deploys agentic AI, GenAI, and LLM-enabled systems for M&A use cases in a regulated enterprise environment. Responsibilities include architecture, coding, testing, CI/CD, security, operational support, environment readiness, risk management, mentoring, code reviews, and stakeholder collaboration.

Leads strategic sourcing and contracting, including supplier negotiations, client agreement portfolios, value realization, financial analysis, and process improvement. Oversees sourcing strategy, contract lifecycle management, supplier relationships, and cross-functional stakeholder engagement. Develops leaders, manages organizational change, champions responsible AI-enabled transformation, and drives measurable savings, revenue, operational efficiency, and client return on investment.

Leads strategy and business development for Verizon’s AI Connect program, including infrastructure market development, GTM partnerships, growth initiatives, supply chain risk reduction, organizational scaling, governance, OKRs, and resource planning. Partners with Legal, Sourcing, Real Estate, Regulatory, and Product teams while guiding the organization from initial build-out through scale and optimization. The role requires executive leadership in high-tech or telecommunications environments and involves more than 50% travel.

Build and manage strategic relationships with AI assistant partners such as Gemini and ChatGPT. Lead consultative discovery, connect partner needs to Amadeus solutions, develop commercial opportunities, create account plans, prepare proposals, support complex negotiations, and share market insights. The role collaborates with Product, Product Marketing, Engineering, and internal stakeholders to shape AI-enabled travel solutions and sustainable commercial outcomes.

Designs and implements scalable Azure cloud architectures, automates infrastructure provisioning with Terraform, and oversees Azure DevOps CI/CD pipelines. Provides technical guidance, troubleshoots complex infrastructure issues, and optimizes cloud environments for performance, cost, security, and compliance. Collaborates with stakeholders and cross-functional teams, documents architecture and processes, conducts environment assessments, and delivers Azure training while driving cloud innovation and business objectives.

Develop and maintain full-stack applications using Java, Spring Boot, React, and TypeScript. Build REST APIs, microservices, cloud-native solutions, and generative AI capabilities involving LLMs, RAG, and AI agents. Participate in the full software development lifecycle, including testing, deployment, monitoring, and production support. Collaborate with cross-functional teams while following secure coding, DevOps, CI/CD, cloud operations, risk, compliance, and AI governance standards.

Build and operationalize AI-enabled data products, agents, and reusable enterprise patterns using governed data platforms. Develop Snowflake and Databricks AI solutions, semantic grounding, retrieval-augmented generation, orchestration, guardrails, evaluations, observability, and production controls. Create reference architectures and implementation playbooks, evaluate emerging tools, and guide teams toward secure, scalable adoption. Partner with governance, risk, security, architecture, and data teams while mentoring practitioners and supporting responsible AI enablement across the enterprise.

Design and deploy autonomous multi-agent AI workflows integrating LLMs with enterprise databases, APIs, and long-term memory. Build orchestration, RAG, evaluation, observability, guardrails, and production microservices using scalable asynchronous patterns. Develop secure, reliable agentic systems with human-in-the-loop escalation and enterprise search integrations. Collaborate on NLP, AI integration, search relevance, contact center platforms, and customer-focused solutions.