Artificial Intelligence Jobs in Richardson, TX

Supports consulting clients in identifying, prioritizing, and implementing Generative AI solutions. Responsibilities include facilitating workshops, analyzing requirements and processes, supporting proof-of-concepts, exploring data, developing documentation, testing solutions, tracking project plans, translating business needs into technical specifications, and delivering GenAI training. The role emphasizes Microsoft AI technologies, prompt engineering, Agile and SDLC practices, continuous AI learning, and client collaboration.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core. Responsibilities include designing vector and matrix-processing engines, optimizing power, performance, area, and timing, developing detailed specifications, supporting functional verification, debugging simulations, and partnering on physical design validation. The role requires expertise in high-performance processor architecture, datapath design, vector and matrix processing, and hardware design languages.

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

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.

Design and implement production-grade backend services and platform APIs in Go. Build Kubernetes-native components (controllers, operators, CRDs, webhooks), integrate with CI/CD, observability, and security systems, and apply AI/agentic programming to automate platform workflows and improve developer productivity. Troubleshoot distributed systems and participate in architecture reviews.

Act as primary technical partner for enterprise customers, troubleshoot complex issues across contact center platforms and integrations, coordinate escalations, leverage AI tools for insights, drive customer outcomes, share feedback with Product/AI teams, mentor peers, and shape AI-augmented support processes.

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.