Artificial Intelligence Jobs in Plano, TX

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.

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.

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.

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.

Supports enterprise application and process improvement initiatives across Supply Chain, Finance, Accounting, Retail, Data, and Technology. Responsibilities include documenting processes and system issues, analyzing gaps, supporting application enhancements, testing improvements, exploring AI automation, conducting data analysis, and coordinating projects. The intern collaborates with cross-functional teams and gains exposure to enterprise platforms and business operations.

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.

Leads enterprise operational risk assessments, evaluates risk exposure and controls, monitors trends and gaps, documents resolutions, and provides practical recommendations. The role partners across functions to understand business processes, assess emerging risks, and support governance and informed decisions in a highly regulated environment.

Supports next-generation AI memory and system architecture by researching infrastructure trends, analyzing HBM bandwidth and latency requirements, developing simulation frameworks and performance models, and building trend dashboards. Collaborates with senior engineers across design and product teams to evaluate AI workload behavior, memory hierarchy trade-offs, GPU/CPU interactions, and architectural opportunities.

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.

Develops scalable, secure, and resilient Java or Python systems within an IAM team. Responsibilities include software design, coding, testing, troubleshooting, architecture documentation, data analysis, and operational stability. Leads responsible adoption of AI-assisted engineering tools, establishes validation and security standards, coaches engineers, and partners with architecture, data science, risk, compliance, and business teams.

Apply statistical, machine learning, and causal inference methodologies to analyze large datasets and solve complex business problems. Develop predictive models, identify trends and correlations, generate actionable recommendations, and build prototype solutions. Collaborate on innovative ideas and communicate analytical findings through presentations and technical documentation for senior management and regulatory review.

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.

Leads software engineering and AI/ML delivery for large-scale risk technology systems. Designs complex architectures, develops secure production code, optimizes Spark clusters and data pipelines, and applies Python, PySpark, SQL, AWS, and Databricks. Establishes AI-assisted engineering governance, improves software quality and automation, analyzes large datasets, and leads technologists in delivering resilient, scalable applications.

Leads development of resilient, scalable software and AI/ML platform services using Python and Java. Drives AI-assisted engineering practices, mentors teams, integrates enterprise systems, and builds fraud-detection and risk-assessment ML pipelines. Designs feature-store, model deployment, monitoring, and agentic AI components with production guardrails, governance, security, and auditability. Collaborates with architects, data scientists, business stakeholders, and infrastructure teams in an agile environment.

Lead and mentor an agile engineering team to design, build, test, and operate secure, cloud-native production software. Provide technical direction, deliver high-quality code, drive product design decisions, and advocate firmwide engineering practices while applying AI/ML expertise.

Supports financial crime compliance through AML transaction-monitoring implementation, model tuning, data analysis, validation, investigations, and control testing. Develops AML analytics using statistical measures and machine-learning algorithms, helps integrate AI into surveillance models, documents requirements and project artifacts, and prepares testing reports and corrective action plans. Collaborates with technology, operations, and business teams while managing data mapping, regulatory documentation, and workflow execution.

Drive adoption and value realization for Cisco Security solutions across a portfolio of mid-sized customers. Build Technical Adoption Plans, deliver technical enablement and demos, manage test environments, troubleshoot issues, facilitate alignment workshops, and use AI-driven insights to improve product utilization. Develop trusted customer relationships, support renewals and CSAT, collaborate with Support, Sales, Engineering, Partners, and Product teams, and provide customer feedback to improve Cisco offerings.

Leads enterprise transformation and product lifecycle initiatives within Merchant Services. Defines business outcomes, prioritizes AI and automation opportunities, redesigns workflows, drives organizational adoption, establishes success metrics, embeds risk and regulatory controls, and leads operating-model and organizational changes. Partners with senior leaders and cross-functional teams while building transformation capabilities through training, coaching, change communities, and managed portfolios.

Develop AI/ML proofs of concept and deployable models for compliance and operational risk analytics. Responsibilities include analyzing structured and unstructured data, designing methodologies, building scalable models and data pipelines, applying machine learning, graph learning, LLMs, and agentic solutions, and documenting quantitative models for governance and validation. The role collaborates with data scientists, technology teams, risk professionals, and model validation groups in a regulated financial-services environment.

Leads enterprise full-stack software engineering for secure, scalable managed-account platforms. Owns application components across architecture, development, testing, deployment, observability, and production support. Designs distributed cloud-native systems using Java and modern frontend technologies, mentors engineers, improves CI/CD and test automation, and drives responsible adoption of AI-assisted development tools. Partners with cross-functional stakeholders to deliver high-impact initiatives in an agile environment.

Provides legal advice and strategic guidance for residential mortgage origination, including conventional, government-insured, jumbo, high-net-worth, and customized lending products. Advises business, compliance, risk, operations, and product teams on mortgage laws, regulatory requirements, product development, underwriting, disclosures, advertising, digital applications, and secondary-market eligibility. Supports audits, examinations, investigations, litigation, remediation, and technology modernization initiatives.