Artificial Intelligence Jobs in Richardson, TX

Participate in a rotational analyst development program focused on using data and technology to analyze performance trends, identify business opportunities, and support insurance operations. Complete training, mentorship, and rotational assignments while developing strategic, technical, analytical, communication, and business skills. Use tools such as Excel, SQL, Python, R, SAS, Snowflake, Power BI, and emerging AI technologies to generate business insights.

Leads the design and development of scalable software frameworks and secure production code. Architects enterprise AI-enabled engineering workflows, establishes responsible AI guardrails, and improves automation, testing, release readiness, and incident response. Advises cross-functional teams, influences senior stakeholders, defines target-state AI architectures, and guides roadmaps and solution architectures across Consumer and Community Banking.

Partners with Sales leadership and HR teams to execute talent strategies, performance cycles, feedback programs, organizational design, and complex HR issue resolution. Advises senior leaders, coaches managers, improves organizational effectiveness, and applies AI-driven HR solutions and people analytics to increase efficiency and business performance.

Leads full-stack software engineering teams and a portfolio of technology projects focused on developer experience, distributed systems, microservices, and cloud-native platforms. Sets technical strategy, oversees large-scale system design and delivery, manages engineering leaders, develops talent and succession plans, and aligns roadmaps with enterprise goals. The role involves Java, Python, cloud platforms, databases, containers, APIs, Agile delivery, and emerging AI technologies.

Lead day-to-day program management and delivery of Client Onboarding & Service transformation initiatives. Scope problems, design solutions, plan delivery, produce executive-ready presentations, drive cross-functional alignment, manage change, engage product and tech teams using agile practices, and apply emerging tech insights to improve outcomes.

Leads cybersecurity engineering teams developing enterprise security solutions across multiple technology domains. Clarifies security requirements, supports multi-level network security, performs threat modeling and vulnerability assessments, and advises leaders during security risks. Uses and validates enterprise-authorized AI for risk analysis, documentation, security testing, and control validation while ensuring data sensitivity, auditability, and resiliency. Coaches, develops, hires, and recognizes engineering talent.

Lead financial planning, forecasting, reporting, business case modeling, and cost optimization for public cloud and AI infrastructure. Partner with technology, finance, planning, and product leaders to improve spending transparency, develop chargeback methodologies, manage financial risks, and support executive decision-making. The role drives cloud financial management transformation and enterprise-wide efficiency initiatives.

Leads security engineering for SaaS Intelligence, including scalable SaaS application onboarding, connector development, integration validation, testing, quality controls, governance, and incident remediation. Manages engineering delivery, resources, budgets, and stakeholder relationships while developing engineers and enforcing standards for code, APIs, security, AI-assisted workflows, resiliency, and auditability.

Leads complex technology projects and programs across Asset and Wealth Management. Responsibilities include planning, resource and budget optimization, stakeholder communication, risk management, governance reporting, requirements clarification, Agile delivery, and continuous improvement. The role also promotes responsible use of enterprise-authorized AI for project planning, software development, testing, code review, and incident analysis, while ensuring validation, security, and appropriate data handling.

Leads technology risk and controls for infrastructure platforms by identifying, assessing, reporting, and mitigating operational and compliance risks. Evaluates control effectiveness, manages governance and issue remediation, advises technology process owners, and communicates risk posture to senior stakeholders and regulators. Uses validated enterprise AI capabilities to streamline risk evidence synthesis, control testing, and executive reporting while maintaining security, auditability, and regulatory compliance.

Leads a team overseeing operational and compliance controls for a banking operations product organization. Provides strategic guidance on responsible AI adoption, identifies and manages operational and technology risks, strengthens governance and control practices, resolves control gaps, and communicates risk insights to senior management. The role also leads strategic initiatives, partners with stakeholders, develops talent, and drives improvements to the control environment.

Supports technology operations and AI automation for cellular networking workflows. Identifies manual processes, documents requirements, develops scripts, applications, dashboards, integrations, and automation frameworks, and prototypes AI-assisted solutions. Cleans and validates operational data, performs testing, documents solutions, monitors deployments, and resolves issues. Collaborates with RAN engineering, construction, field operations, project management, and business teams while following cybersecurity, privacy, access-control, confidentiality, and responsible-AI requirements.

Leads architecture and engineering for consolidating global wide area networks into a unified platform. Defines carrier-scale routing, traffic engineering, resiliency, automation, telemetry, validation, and AI-assisted operational strategies. Oversees transformation plans, migrations, production rollouts, technical standards, risk controls, and reliability improvements while partnering across engineering, infrastructure, cloud, security, operations, and architecture teams.

Lead cybersecurity strategy and architecture across products, applications, and technologies. Advise engineering teams, communicate complex risks to leadership, develop reusable security frameworks, create mitigation solutions, and evaluate emerging technologies. The role requires influencing cross-functional teams, shaping enterprise-wide architecture, and applying cloud-native, application, API, web, and mobile security expertise across a complex financial-services environment.

Entry-level technology program participants complete a six-month training and development experience before joining an engineering team. They build, test, and debug software, contribute to agile projects, practice code quality and security, learn modern architecture, and use AI-assisted development tools. The program emphasizes mentorship, collaboration, continuous learning, systems thinking, and delivering customer-focused software solutions.

Develop Generative AI solutions for financial services using Python, PyTorch, LangChain, AWS, Spark, vector databases, multi-agent systems, and advanced RAG pipelines. Build, fine-tune, evaluate, validate, and deploy machine learning models across large numeric and textual datasets. Collaborate with data scientists, machine learning engineers, and product managers while translating technical findings into business outcomes.

Develop and test integration services, automated recompilation tools, data-mapping scripts, microservices, and software automation. Recompile legacy code into Java, create Helm Charts for Kubernetes deployments, execute integration test cases, and collaborate in an Agile environment. The intern will also support data security, privacy, compliance, and operational processes.

Leads AI/ML and generative AI product initiatives for Chase Travel, identifying opportunities, prioritizing roadmaps, managing Agile delivery, and developing requirements. Partners with cross-functional teams across technology, design, analytics, risk, legal, compliance, marketing, and operations. Evaluates product metrics, conducts user and market research, drives process automation and innovation, and communicates AI’s impact to stakeholders.

Leads the design, engineering, and delivery of production-grade agentic AI solutions for mainframe and midrange infrastructure management. Owns architecture, implementation, testing, rollout, monitoring, resiliency, security, and operational readiness. Partners with SRE, operations, risk, and architecture teams to ensure governance and reliability. Evaluates tools and vendors, communicates technical decisions, and mentors engineers while driving automation and reducing operational toil.

Leads software engineering initiatives within an agile banking technology team. Designs, develops, reviews, debugs, and troubleshoots secure production code; drives responsible AI-assisted development practices; improves automation and operational stability; evaluates architectures and vendors; and promotes modern engineering technologies. The role requires advanced programming, generative AI and machine learning familiarity, distributed systems, cloud platforms, microservices, APIs, databases, containerization, performance testing, and chaos engineering experience.

Lead the architecture and evolution of enterprise developer telemetry and real-time data platforms. Build scalable streaming pipelines, AI inference capabilities, data lake solutions, observability frameworks, and privacy controls. Correlate AI engineering metrics with business outcomes while mentoring engineers, shaping technical strategy, evaluating build-versus-buy decisions, and contributing directly through prototypes, code patterns, and reusable data products.

Design, deploy, and scale production AI/ML solutions for healthcare, including predictive models, generative AI, statistical analysis, microservices, APIs, and MLOps pipelines. Analyze complex clinical datasets, implement model monitoring and governance, evaluate emerging AI technologies, and collaborate with engineering, data, product, and clinical teams to improve care delivery and operational efficiency.

Leads infrastructure engineering initiatives across cloud, mainframe, and midrange environments. Designs and maintains secure, production-grade agentic AI solutions for infrastructure automation, validates AI-assisted recommendations, and ensures resiliency, auditability, compliance, and operational excellence. Partners with SRE, operations, architecture, risk, and control teams; evaluates tools and vendors; modernizes processes; and mentors engineers through technical reviews and coaching.

Lead and execute an AI-driven automation and data strategy for global hyperscaler delivery programs. Define roadmap, prioritize use cases, lead a matrixed global team to build scalable automation tooling, enable AI/ML-driven operations, define data standards and metrics, and partner with engineering and commercial teams to industrialize and measure automation ROI.

Leads software engineering efforts for secure, scalable banking technology. Designs, develops, tests, debugs, and reviews production code while guiding teams in responsible AI-assisted development. Applies Java, cloud, microservices, distributed systems, generative AI, performance testing, and chaos engineering practices. Evaluates technical solutions with vendors and internal teams, automates recurring remediation, improves operational stability, and leads engineering communities of practice.