Artificial Intelligence Jobs in Richardson, TX

Design, build, and operate AI-enabled GTM workflows and consolidate technical ownership of marketing platforms (Marketo, Outreach, Bizible, Asana, Salesforce). Build API integrations, automation scripts, and lightweight internal tools; support platform governance, documentation, data hygiene, and AI literacy across Marketing.

Lead AI/ML-focused information security for enterprise agentic capabilities. Advise projects and CSOC teams on threat mitigation, compliance, automation, monitoring, and incident response. Partner with engineering and stakeholders to secure cloud, generative AI, and customer servicing platforms while driving data-driven decisions and continuous improvements.

The Senior Product Owner leads product development for Mainframe solutions at Broadcom, collaborating with cross-functional teams to deliver features based on customer needs and product roadmaps.

Lead design, enhancement, and maintenance of the bank's data warehouse and analytical platforms. Drive data engineering best practices, support ML/predictive capabilities, manage production issues, automate processes, collaborate on feature design, and mentor engineering teams while partnering with PMO on Agile delivery.

Lead vision, strategy, and roadmap for Open Mainframe Solutions (Zowe and related tools). Advocate customer needs to R&D, prioritize features, unblock cross-functional teams, drive GTM and adoption, measure KPIs, and maintain executive and customer relationships to ensure product success.

Lead and support IT and AI sourcing from intake through contract execution: develop sourcing strategies, run RFx events, perform spend and market analysis, negotiate vendor and software agreements, manage vendors, collaborate with Legal/Finance/Technology, drive cost savings and process efficiencies, and present recommendations to stakeholders and leadership.

Lead design, deployment, and maintenance of large-scale Generative AI solutions (RAG and Agentic AI). Architect secure document processing pipelines, integrate responsible AI practices (toxicity/bias screening), implement data security and compliance, monitor AI infrastructure, and collaborate with cross-functional governance and legal teams.

Design, build, and scale AI-powered operational platforms integrating LLMs, monitoring, CI/CD, ticketing, and cloud services. Develop APIs, data pipelines, front-end apps (TypeScript/React/Next.js), backend systems, evaluation/observability tools, and reusable frameworks. Collaborate across SRE, Product, and Infrastructure to deliver production-grade, automated AI workflows and improve system reliability and performance.

Lead global content strategy and team to improve discoverability and AI visibility across web, product, and partner ecosystems. Own GEO/SEO, structured data, content governance, taxonomy, onsite search relevance, agency management, measurement, and cross-functional execution to ensure authoritative, machine-readable content that drives business impact.

Lead design and implementation of LLM-based application patterns, prompts, agentic workflows, RAG pipelines, evaluation frameworks, safety guardrails, and developer tooling. Mentor teams, conduct red-teaming, optimize latency/cost/quality trade-offs, and translate LLM research into reusable organizational standards and production-ready systems.

Build and operate petabyte-scale data pipelines for AI training and evaluation: ingestion, cleaning, deduplication, versioning, lineage, high-throughput loading, labeling workflows, privacy enforcement, observability, and cost/performance optimization while collaborating with ML teams.

Design and ship production-quality ML systems from research to deployment. Prototype and evaluate models across NLP, vision, recommendation, and structured data. Build training/inference pipelines, implement rigorous experiments and monitoring, optimize for accuracy and latency, and ensure safety, fairness, and reliability. Partner with product and platform teams, document findings, mentor engineers, and influence AI roadmap.

Lead and scale integration engineering for pharmacy and consumer wellness lines by embedding AIOps, AI/ML and automation across cloud-native platforms (Azure/AWS/GCP). Own modernization, API orchestration, CI/CD, testing and ML model validation; drive roadmaps, budgeting, vendor partnerships, hiring, and OKRs to ensure resilient, cost‑optimized, high‑quality delivery and proactive incident management.

Lead incident management and site reliability initiatives, implement SRE practices and SLAs/SLOs, deploy AIOps-driven detection and self-healing automation, drive observability using Dynatrace, and enhance ITSM processes via ServiceNow while partnering across NOC, Cloud, DevOps, and application teams.

The CTO will lead technology modernization efforts, drive innovation in cloud computing and analytics, and oversee the transformation of core insurance platforms to enhance customer experiences and business growth.

The Chief Compliance Officer will drive operational excellence and oversee regulatory compliance while managing investment operations and financial oversight.

Provide Tier 3 SailPoint IdentityIQ and ISC operational support while building and operationalizing AI/LLM-assisted tooling (RAG, triage, summaries) to reduce manual effort, improve consistency, and maintain audit‑sensitive governance. Collaborate with IAM leadership, engineering, product, security, and application teams to validate entitlements, resolve complex identity issues, and scale IAM operations.

As a Staff Software Engineer, you will lead technical strategies, develop APIs and microservices, and mentor engineers for innovation at GEICO.

Design, develop, test, and support scalable AI-enabled applications and services. Implement LLM, Generative AI, and RAG capabilities, build RESTful APIs and microservices, automate CI/CD and testing, perform code reviews, troubleshoot production issues, and collaborate with product and architecture teams in Agile delivery.

Lead architecture, delivery, and modernization of scalable full-stack applications with AI-native workflows. Drive adoption of AI-assisted development, mentor engineering teams, establish standards (CI/CD, governance), integrate AI services, and support production reliability and performance.

Lead development and delivery of Fannie Mae's enterprise AI platform capabilities, balancing innovation with security, governance, and cost controls. Own product vision, roadmaps, and core services (models, tooling, agent runtimes), partner with engineering, security, finance, legal, and business teams, onboard priority use cases, and drive adoption through strong stakeholder engagement and developer experience.

Develop and deploy end-to-end ML solutions for smart manufacturing: build data pipelines, feature engineering, CV and LLM-based models (RAG/agentic workflows), prototype and productionize models, implement monitoring/retraining, and collaborate with cross-functional teams using modern development and CI/CD practices.

Lead firmwide AI enablement by setting strategy and roadmap, designing multi-level training, running an AI champion community, producing adoption analytics, shaping governance, evaluating tools and vendors, and managing stakeholders and a small team to drive responsible AI adoption and measurable business impact.

The AI Engineer will prototype AI solutions, advise on integration, manage AI initiatives, and collaborate across technology teams, ensuring alignment with business needs. Roles include monitoring AI trends, engaging stakeholders, and conducting knowledge-sharing sessions on best practices.

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