Artificial Intelligence Jobs in Richardson, TX

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.

Leads software engineering teams and complex technology initiatives within Operations Collections. Establishes governance for agentic AI-enabled engineering, SDLC automation, quality controls, security, resiliency, and traceability. Directs technical strategy, budgets, resources, talent development, cloud-native solutions, and cross-functional delivery while influencing senior stakeholders and enabling reusable solutions across business domains.

Leads development of secure, scalable, cloud-native full-stack applications using Java, Spring Boot, Python, React, and modern architecture patterns. Designs microservices, REST integrations, authentication solutions, data models, and resilient systems; writes and reviews production code, troubleshoots issues, automates remediation, and promotes zero-downtime delivery. Leads adoption of responsible AI-assisted engineering practices, mentors engineers, drives communities of practice, and supports continuous technology modernization.

Leads the strategy, governance, adoption, and continuous improvement of Production Management tools supporting enterprise application and infrastructure services. Oversees observability, incident, problem, change, event, resilience, reporting, workflow, and risk-management capabilities. Drives responsible adoption of Claude Code, GitHub Copilot, NowAI, and other AI solutions to improve operational insight, automation, service stability, and incident response. Partners with technology owners and senior stakeholders to define roadmaps, metrics, integrations, controls, and continuous-improvement initiatives.

Leads architecture and hands-on delivery of complex backend, UI, API, and production AI applications. Owns ADK and LangGraph agentic workflows, establishes engineering standards, drives resiliency and operational readiness, and mentors engineers. Partners across Product, Design, Security, and SRE to deliver secure, scalable systems using Python, React, AWS, FastAPI, databases, CI/CD, and modern software engineering practices.

Leads complex, cross-organizational technical programs that institutionalize AI product development lifecycle practices and scale agentic engineering. Responsibilities include defining AI governance, reference architectures, evaluation frameworks, guardrails, observability, risk controls, and delivery standards. Partners with engineering, product, data, cybersecurity, compliance, audit, and risk teams to improve AI delivery flow, manage dependencies, advise senior leaders, and measure outcomes across multi-quarter transformation programs.

Supports AI-first process improvement and transformation engagements by analyzing processes and data, building prototypes and agentic workflows, documenting business logic, developing recommendations, and communicating solutions to technical and non-technical stakeholders. Works under senior guidance while developing technical credibility, applying generative AI responsibly, considering adoption and change management, and delivering assigned workstream outcomes. Travel may be required up to 10%.

Leads the design, development, and delivery of secure, scalable software and production AI applications using Python, ADK, and LangGraph. Owns system architecture, API standards, microservices, quality controls, guardrails, testing, resiliency, and operational readiness. Partners with Product, Security, SRE, and engineering teams while driving CI/CD, security scanning, dependency management, and SDLC improvements. Provides technical leadership through design reviews, stakeholder alignment, code reviews, and mentoring.

Lead design, build, and deploy enterprise-grade AI solutions (RAG, agentic systems, LLM integrations). Use AI-assisted development tools daily, architect scalable secure systems on AWS, write production code, own end-to-end outcomes, evaluate vendors, and drive cross-team alignment and automation to improve operational stability.

Lead design and production of generative and agentic AI solutions, build ML pipelines and MLOps, define enterprise semantic modeling and ontology governance, implement RAG and responsible AI practices, and mentor engineers while partnering with stakeholders to deliver measurable business outcomes.

Lead development of secure, scalable Java full-stack applications for mortgage technology. Design, develop, test, troubleshoot, review, and debug production code; improve operational stability through automation and remediation. Drive responsible adoption of enterprise-approved AI-assisted development tools, establish validation and security standards, coach engineers, and evaluate vendor and architectural solutions. Collaborate within agile teams using SDLC, CI/CD, resiliency, and security practices.

Build rapid AI prototypes, applications, point solutions, and agentic workflows alongside client engagement teams. Translate business challenges into working solutions, validate feasibility, align stakeholders, and hand off prototypes to Product and Technology. Guide teams in adopting AI-first approaches using approved platforms, controls, and guardrails. Capture business logic, support change management, connect clients with AI product teams, and teach technical practices through hands-on collaboration.

Designs, deploys, maintains, and troubleshoots HPE NonStop payment infrastructure, secure key managers, Etinet servers, and related subsystems. Uses AIOps and AI-assisted practices for incident triage, anomaly detection, automation, documentation, and reliability improvements. Partners with SRE, observability, and cybersecurity teams to govern AI-enabled monitoring, maintain auditability, execute upgrades, and produce operational knowledge such as runbooks and troubleshooting guides.

Lead software and ML engineering for scalable, secure production systems. Author and review code, drive AI-assisted engineering practices, design ML pipelines and deployment/monitoring, automate remediation, evaluate vendors, and mentor teams on responsible AI and MLOps.

Leads large-scale AI and machine learning initiatives, defining problem statements, roadmaps, and production solutions. Develops NLP, generative AI, recommendation, personalization, search, and document question-answering models. Builds scalable batch and real-time ML pipelines on AWS, collaborates with product, engineering, business, legal, and compliance teams, and communicates technical results to senior stakeholders. Oversees experimentation, model evaluation, deployment, and team performance.

Design, develop, and operate a production agentic data platform using Spark, Kafka, Airflow, Snowflake and AWS. Write secure high-quality code across frontend and backend, leverage enterprise AI-assisted development and LLMs (Claude Code, agents, RAG, embeddings), build autonomous agents and MCP server components, apply secure/responsible AI practices, troubleshoot systems, and own full-stack application/platform delivery with CI/CD, containers, and observability.

Leads the design, development, testing, troubleshooting, and delivery of scalable Java software systems for Identity and Access Management. Produces architecture artifacts, applies secure coding and non-functional requirements, mentors engineers, and drives Agile delivery. Leads adoption of enterprise-approved AI-assisted development tools, establishing standards for validation, security, and responsible use. Collaborates with stakeholders, evaluates system dependencies, and implements continuous improvements across software delivery and automation practices.

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.

Lead design and deliver AI-enabled data platform capabilities (metadata, lineage, data quality, retention). Drive adoption of enterprise-authorized AI-assisted engineering, build agentic production systems, develop secure production code, automate remediation, establish production SRE controls, and mentor teams on responsible AI and validation standards.

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.