Artificial Intelligence Jobs in Plano, TX

Lead design, development, and production deployment of advanced AI/GenAI and LLM solutions. Build and tune models, integrate generative AI into ML platforms, drive MLOps adoption, ensure responsible AI governance, collaborate cross-functionally, and mentor AI engineers.

Build and lead production Python software for technology-risk oversight, including data pipelines, PostgreSQL systems, authenticated APIs, and LLM agent workflows. Develop RAG, tool orchestration, evaluation, and guardrails; ensure security, auditability, observability, testing, reliability, and responsible AI use. Collaborate with Product, Risk, Controls, Compliance, and data teams while delivering dashboards and evidence packages.

Summer Analyst in Data & AI will design and build end-to-end data, analytics, and ML/AI solutions using cloud and modern tooling. Responsibilities include developing models and pipelines, running experiments tied to business KPIs, supporting data governance and compliance, creating dashboards, and collaborating in agile teams while receiving mentorship and training.

Leads Smart Manufacturing and IT for a 300mm semiconductor wafer fab. Partners with factory leadership to deliver technology roadmaps, manufacturing systems, equipment automation, AMHS, robotics, reliability, digital transformation, and AI-enabled solutions. Oversees a multidisciplinary engineering organization, production-critical IT availability, incident response, vendor coordination, portfolio prioritization, and adoption of technologies that improve capacity, quality, productivity, cycle time, yield, cost, and factory resilience.

Lead engineering teams and technology projects that build reliable, cloud-native, full-stack systems. Design and implement distributed microservices, APIs, databases, and shared cloud platforms using Java, Python, AWS, containers, and modern AI tools. Provide technical leadership on architecture, resilience, observability, performance, coding standards, platform roadmaps, and enterprise technology strategy while mentoring engineers and partnering with product and architecture leaders.

Architect and build scalable, secure cloud infrastructure for SaaS platforms. Lead CI/CD automation, Kubernetes-based microservices scaling, infrastructure-as-code adoption, cross-functional DevOps projects, and AI-assisted operational improvements. Collaborate with engineering, QA, and product teams to improve delivery, reliability, cost efficiency, and developer productivity. Participate in on-call rotation and serve as a DevOps subject matter expert.

Lead full-stack software engineering initiatives and developer teams building distributed, cloud-native systems and developer experience platforms. Design architectures, implement high-reliability services, shape technology roadmaps, mentor engineers, and collaborate with product and architecture leaders. Work with Java, Python, front-end frameworks, APIs, databases, Docker, Kubernetes, cloud platforms, CI/CD, infrastructure as code, automated testing, observability, and AI-based development tools.

Leads full-stack software engineering initiatives using cloud technologies, distributed microservices, databases, APIs, and modern programming languages. Provides technical direction across Agile teams, mentors engineers, partners with architects and product managers, establishes engineering standards, improves system performance, reduces technical debt, and evaluates emerging technologies including AI-based development tools.

Build and lead full-stack software engineering projects using Java, Python, cloud platforms, microservices, databases, containers, and AI-enabled development tools. Provide technical leadership across Agile teams, define service architectures and integration patterns, improve system performance, reduce technical debt, establish engineering standards, mentor developers, and deliver secure cloud-based solutions supporting enterprise and regulatory needs.

Leads AI networking channel growth across HPE’s Campus and Branch portfolio by activating partners, generating pipeline, developing opportunities, and driving revenue. Provides technical guidance, solution positioning, competitive differentiation, partner enablement, workshops, proofs of concept, and managed-services readiness. Collaborates with account managers, engineers, distributors, business units, and regional teams to execute sales initiatives, increase AI networking and software adoption, support competitive displacement, and influence partner investment and go-to-market strategies.

Build, deploy, test, scale, and optimize machine learning models and AI inference workflows for edge and cloud environments. Develop maintainable software components and APIs, profile performance, document engineering designs and benchmarks, and communicate technical trade-offs across software, machine learning, and hardware teams.

Owns the prioritized backlog and day-to-day delivery for an Agile scrum team supporting Bank of America’s enterprise Document AI program. Translates business objectives into user stories and acceptance criteria, prioritizes scope, accepts completed work, manages stakeholders, removes ambiguity, and supports scalable AI capability adoption while ensuring quality, regulatory alignment, and delivery commitments.

Leads AI and policy governance, business controls, risk oversight, and quality assurance within a financial-services enterprise. Responsibilities include managing AI opportunity pipelines, coordinating risk assessments and approvals, monitoring and testing controls, overseeing remediation, developing governance routines and reporting, supporting audits and regulatory exams, and advising senior stakeholders on operational risk, compliance, and responsible AI adoption.

Leads global financial analysis and portfolio management for public cloud and artificial intelligence infrastructure rate optimization. Responsibilities include evaluating compute, database, and GPU commitments; developing financial models, forecasts, scenarios, and business cases; tracking utilization and savings; analyzing month-end results; managing implementation changes; and preparing executive-ready reporting and presentations. Partners across finance, technology, controllership, and strategic sourcing to improve efficiency, governance, and infrastructure spending outcomes.

Lead development of agentic AI platform capabilities, including orchestration frameworks, RAG systems, tool calling, memory management, APIs, and production deployment patterns. Drive architecture, platform roadmaps, reliability, monitoring, governance, privacy, model risk controls, and responsible AI practices. Partner with product, engineering, risk, and control teams while coaching engineers on secure AI-assisted development and communicating technical strategy to senior stakeholders.

Lead development of agentic AI platform capabilities, including orchestration frameworks, retrieval systems, APIs, SDKs, reference implementations, memory management, tool calling, and production deployment. Define platform roadmaps, architecture, reliability, monitoring, testing, governance, privacy, and model-risk standards. Partner with product, engineering, risk, and control stakeholders while guiding responsible AI-assisted software development and communicating technical strategy to senior leaders.

Early-career engineer responsible for characterizing AI/ML training and inference workloads, analyzing compute and memory bottlenecks, and building performance models for hardware and software systems. The role partners with architecture, compiler, runtime, and product teams on optimization decisions, benchmarking, and reproducible technical analyses. Candidates apply mathematical reasoning, computer architecture knowledge, Python-based data analysis, and machine learning frameworks. Travel is required up to 10%.

Lead technical sales engagements with AI platform, hyperscale, service provider, and data center customers. Design large-scale networking architectures, demonstrate Cisco solutions, connect technical strategy to account objectives, and drive demand generation and enablement. Advise on routing, optical systems, compute, storage, silicon, AI workloads, automation, and MLOps while building customer trust and coordinating stakeholders to deliver business outcomes.

Leads AI product solutions from pilot through production across multiple business domains. Develops AI enablement strategies, strategic and tactical roadmaps, feature backlogs, business cases, and user experiences. Partners with business stakeholders, data scientists, engineers, architects, and UX teams to prioritize needs, design solutions, manage dependencies, measure KPIs, mitigate risks, and deliver business value. Guides teams, communicates complex concepts to senior leaders, and mentors team members.

Owns and prioritizes AI product backlogs, translating business needs into features and user stories for data science and AI engineering teams. Manages delivery risks, dependencies, controls, testing, releases, and stakeholder alignment across the AI development lifecycle. Partners with cross-functional teams to deliver compliant AI solutions from pilot through production, coaches other Product Owners, and supports process improvement, change adoption, and measurable business value.

Leads the hands-on design, development, deployment, and lifecycle management of AI agents supporting Crowe’s Audit practice. Partners directly with Audit practitioners, builds production-grade Python solutions, establishes agent architecture and engineering standards, implements evaluation and observability, and maintains Azure DevOps CI/CD pipelines. Provides technical leadership, mentoring, project coordination, and product judgment while measuring business impact. The role may grow into managing a small team of forward-deployed engineers.

Engineer and operate AI monitoring, guardrail, observability, and governance applications in an on-premises OpenShift environment. Responsibilities include building APIs and integrations, deploying containerized services, managing model evaluation workflows, developing Grafana dashboards and alerting, troubleshooting production systems, optimizing scalability and performance, and improving controls for agentic AI applications. The role also leads cross-functional initiatives, mentors engineers, and supports operational planning in a regulated enterprise.

Leads end-to-end machine learning engineering, including data pipelines, model development, testing, deployment, APIs, infrastructure, production support, and GenAI applications. Configures AI/ML environments across AWS, GCP, and on-premises systems; develops complex technical solutions and prototypes; establishes implementation patterns; manages risk and compliance; and mentors engineers. The role requires extensive programming, data engineering, MLOps, cloud, and technical leadership experience.

Develop and maintain machine learning systems across the full lifecycle, including data pipelines, model integration, testing, deployment, monitoring, APIs, and production support. Configure AI/ML infrastructure across cloud and on-premises environments, develop GenAI solutions, enforce coding and data standards, conduct code reviews, and manage risk and compliance. Collaborate with data scientists, engineers, and business stakeholders to deliver predictive analytics solutions.

Lead sourcing and contracting for software, SaaS, cloud applications, licenses, and renewals. Partner with stakeholders to define sourcing strategy, run RFx events, evaluate proposals, negotiate commercial and contractual terms, analyze spend and usage to identify savings and risk reduction, and support contract execution using procurement tools and emerging technologies including AI.