Artificial Intelligence Jobs in Richardson, TX

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.

Support finance transformation initiatives by leading a workstream, developing AI solutions for finance teams, analyzing financial and operational data, building business cases, tracking performance metrics, and presenting findings to finance leadership. Prepare concise executive summaries and presentations while collaborating with Finance, Accounting, Commercial, Operations, and transformation teams.

Leads cybersecurity architecture for software applications and platforms within wealth management. Drives secure product design, evaluates current and emerging technologies, establishes target architectures, and guides business and technical stakeholders. Oversees alignment with enterprise frameworks, regulatory requirements, scalability, resilience, and software development lifecycle practices. Serves as a subject matter expert in architecture governance and collaborates across teams to deliver secure, high-volume enterprise solutions.

Owns the roadmap for AI, automation, and process transformation initiatives. Identifies business opportunities, leads discovery workshops and pilots, translates needs into product requirements, and partners with business and technology teams to deliver scalable solutions. Measures adoption, operational impact, customer outcomes, and value realization while supporting governance, security, responsible AI, and organizational change. Requires product ownership experience, property and casualty insurance expertise, Agile/Scrum experience, analytics skills, and strong cross-functional leadership.

Provides first-line information security risk advisory expertise focused on Identity and Access Management. Assesses risks, processes, and controls; advises stakeholders and management on risk resolutions; communicates risk considerations; and supports business decisions in a regulated environment. The role requires applying analytical methods, sound judgment, and business context to strengthen risk management practices and address evolving regulatory expectations.

Lead quantitative and qualitative consumer research for Samsung’s Mobile Division, including brand tracking, segmentation, concept testing, customer experience research, and market assessments. Apply AI and automation to improve research efficiency and insight generation, explore agentic AI applications, and develop responsible-use governance. Partner with Marketing, Product, Customer Experience, Innovation, Analytics, Technology, and Strategy teams to deliver recommendations supporting go-to-market strategy, portfolio optimization, customer engagement, and pricing.

Lead an agile engineering team to design, develop, test, and operate secure, scalable production software. Provide technical guidance, influence product and architecture decisions, deliver high-quality code, and promote firmwide engineering practices and modern cloud-native technologies.

Owns the roadmap, strategy, risk management, and continuous improvement of data platforms supporting financial-crime analytics, detection models, investigations, and AML operations. Responsibilities include requirements gathering, backlog prioritization, agile delivery, data analysis, model lifecycle management, monitoring, issue remediation, governance, and stakeholder communication across business and technology teams.

Senior analytics leader partnering with business and finance to deliver trusted metrics, improve data quality, govern portfolio metrics, and generate decision-ready insights. Leads end-to-end analytics, drives automation and self-service, validates AI use, and communicates executive-level findings to manage lending performance, risk, and operational efficiency.

Build and operate secure, scalable microservices on AWS and Kubernetes. Develop generative and agentic AI capabilities using LLMs, RAG, embeddings, tool calling, and agentic workflows. Apply security across applications, APIs, containers, identity, and data. Automate testing, deployment, and monitoring through DevSecOps practices, troubleshoot production issues, and improve engineering standards while mentoring and collaborating across teams.

Leads global product process excellence and business transformation initiatives, converting drawing-based product knowledge into structured, governed digital definitions. Oversees product configuration, engineering platforms, PLM and ERP integrations, digital thread strategy, process standards, AI adoption, and organizational change. Partners across product development, manufacturing, IT, business transformation, and regional teams to improve data quality, traceability, configuration accuracy, order handoff, and manufacturing readiness.

Own and exceed sales targets across renewals, expansions, and new business for managed security solutions. Prospect, present, close, manage pipelines and forecasts, build client relationships, attend industry events, and collaborate with marketing, legal, technical, and channel teams. The role also involves improving AI-enabled sales tools and traveling domestically and internationally, including to the Netherlands, with potential progression into North American sales leadership.

Lead architecture and development of a firm-wide software dependency risk platform on AWS and Java. Own data ingestion, dependency graph modeling, APIs, integrations, technical strategy, and production delivery. Establish agentic AI engineering practices using tools such as Claude, with governance for security, resiliency, auditability, and human validation. Mentor senior engineers, solve complex technical problems, and represent engineering across security, risk, compliance, and platform stakeholders.

Lead the architecture, development, testing, deployment, and security of scalable Data, AI, and generative AI solutions. Build LLM services, AI agents, chat systems, data models, pipelines, microservices, and APIs using Python, React, cloud platforms, and modern data technologies. Lead testing, deployment, compliance, monitoring, and reliability efforts while collaborating with clients, leadership, and technical teams.

Lead end-to-end development of a greenfield enterprise platform for software dependency risk management. Build Java services, APIs, data ingestion pipelines, dependency analysis capabilities, and developer-facing features on AWS. Guide engineers and teams in secure AI-assisted development, code quality, testing, governance, and operational stability. Provide technical direction, influence architecture and product decisions, support production systems, and collaborate with product managers and designers to deliver scalable platform capabilities.

Build and scale internal generative AI and agentic solutions that improve software engineering productivity. Develop reusable agents, RAG systems, developer tools, orchestration patterns, SDKs, and reference implementations. Partner with engineering teams to prototype and productionize use cases, provide enablement, and establish evaluation, governance, security, privacy, observability, reliability, and cost practices. Contribute to AI adoption initiatives and communicate implementation patterns across technical and nontechnical stakeholders.

Leads the engineering organization for a firm-wide software dependency risk platform. Responsibilities include hiring and managing engineers and engineering managers, owning platform architecture and roadmap on AWS and Java, building data ingestion and dependency graph capabilities, establishing AI-first development practices, and driving responsible AI governance, security, resiliency, and adoption across a complex enterprise.

Leads enterprise technology, architecture, and AI strategy across transformation initiatives. Defines technical roadmaps, architectural standards, governance frameworks, reference architectures, and responsible AI practices. Evaluates emerging technologies, drives proofs of concept and modernization, aligns investments with business priorities, and accelerates AI adoption. Partners with executives and cross-functional leaders, influences technical direction without direct authority, mentors senior engineers and architects, and represents the organization as a technology and AI thought leader.

The Digital and AI Experience Intern partners with Operations teams to identify business problems, conduct user discovery, define problem statements, and build and refine AI-assisted solutions. The role includes testing ideas, gathering feedback, tracking adoption, creating user guides, transitioning solutions to business owners, and presenting outcomes. Candidates gain experience in stakeholder engagement, experimentation, problem-solving, communication, and responsible AI use.

Build and operate full-stack, cloud-based applications for small businesses using React, Node.js, JavaScript/TypeScript, MongoDB, and AWS. Translate ambiguous customer and business needs into requirements, architecture, and acceptance criteria. Use and validate AI-generated work across development, testing, debugging, and documentation. Develop integrations, multi-tenant platforms, domain and DNS capabilities, and business workflows while diagnosing production issues and improving engineering and deployment processes.