Artificial Intelligence Jobs in Richardson, TX

Support the Corporate AI team by gathering requirements, mapping processes, evaluating AI tools, managing intake and KPIs, and producing clear documentation to turn ideas into measurable AI solutions.

As a Senior QA Automation Engineer, you will design automation frameworks, test AI features, and collaborate with developers to ensure high code quality.

Lead end-to-end AI/ML architecture across the organization: define reference architectures, design patterns, and governance; architect data pipelines, feature stores, deployment, monitoring, and MLOps; align with security, infrastructure, and business domains; drive adoption of modern AI capabilities (LLMs, generative AI, vector DBs); mentor teams and communicate technical strategy to stakeholders.

Lead delivery of core platform capabilities from ideation to launch for an enterprise-scale agentic/AI platform. Author specs, prioritize work, run discovery with customers, partner with engineering, UX, and GTM teams, track OKRs, and ensure successful customer enablement. Operate in a fast-moving, AI-focused product environment and adapt plans as business priorities change.

Lead a forward‑deployed AI solutions team to translate enterprise AI capabilities into business outcomes. Partner with executives to co‑design and deliver priority use cases, drive AI productivity tool adoption, establish repeatable AI solution patterns, and feed learnings back into the AI platform and governance. Balance rapid delivery with enterprise rigor while coaching teams and managing stakeholders.

Lead go-to-market strategy for Tanium Atlas and AI-powered automation and governance within the Autonomous IT platform. Define positioning and messaging, engage customers and market to inform product direction, create high-impact content and sales enablement, drive launches and competitive intelligence, and collaborate cross-functionally to increase awareness and adoption.

The Senior AI Cloud Architect will design and deliver AI/LLM-powered cloud applications, lead architectural decisions, and ensure production readiness with a strong focus on scalable solutions.

Lead data and AI strategy engagements: assess current-state data ecosystems, define target-state architectures, governance, operating models, prioritize AI/analytics use cases, build roadmaps and business cases, facilitate executive workshops, and guide delivery and adoption across stakeholders.

Lead architecture and build cloud-native, resilient enterprise software and Agentic/Generative AI solutions for Claims Adjudication. Design microservices, APIs, CI/CD and observability; integrate LLMs, vector stores, and orchestration frameworks; ensure AI governance and production reliability while mentoring teams and aligning technical strategy with business outcomes.

Lead and manage an engineering team to design, build, and operate large-scale distributed systems using cloud and AI technologies. Provide technical oversight, set KPIs/OKRs, own delivery from strategy to execution, recruit and mentor engineers, collaborate cross-functionally, manage risk, and drive continuous improvement and scalable solutions.

Lead architecture and development of scalable Java-based WFM server-side solutions, champion AI-assisted development, drive engineering standards, mentor senior engineers, resolve production issues, and collaborate cross-functionally to deliver enterprise software.

Build infrastructure automation and AI-driven operations for a global multi-region cloud platform. Design end-to-end provisioning pipelines, integrate AI agents for incident intelligence and change-risk scoring, and collaborate with SRE/DevOps to translate manual workflows into secure, compliant automation across sovereign regions.

Develop, validate, and improve machine learning models (regression, classification, forecasting, optimization). Prepare data, perform feature engineering, train and evaluate models, and support deployment with Data/ML Engineering. Communicate results, document methods, and collaborate on experiments and cross-functional initiatives.

Lead design and delivery of scalable, production-grade agentic AI and automation systems integrated with enterprise collaboration tools (Slack, Outlook, Zoom, SharePoint, Copilot). Drive architecture-to-execution, CI/CD, infrastructure-as-code, monitoring, and cross-team collaboration to scale AI-driven workflows and improve associate productivity.

Design, build, and deploy production-ready AI systems and agents using Python and LLMs. Implement RAG pipelines, vector embeddings, and semantic search. Integrate AI features via REST APIs and microservices, apply prompt engineering, monitor performance, and collaborate with cross-functional teams to deliver reliable, scalable AI-powered applications.

Lead and scale a Data & AI Support Engineering team to resolve complex Spark, streaming, Lakehouse, and Databricks issues. Build AI-enabled support workflows, automations, and runbooks; partner with Engineering/Product to operationalize diagnostics and observability; manage KPIs, escalations, hiring, training, and on-call incident response while acting as a technical escalation leader for enterprise customers.