Artificial Intelligence Jobs in Plano, TX

Support traded-products counterparty credit risk analysis by monitoring exposures, sizing limits, and improving exposure methodologies and tooling. Partner with sales, trading, credit officers, quantitative research, technology, and operations to perform deep dives, report risks, form risk appetite views, and drive AI-enabled workflow improvements and firmwide initiatives.

Develop and prepare multi-dimensional semiconductor layouts from schematics, lead major block developments, verify data integrity, debug physical verification issues, mentor juniors, improve automation and layout methodologies, and coordinate with global design, verification, and CAD teams.

Lead enterprise payments architecture for card-present solutions, provide technical governance and guidance, integrate AI-enabled capabilities securely, develop and review production code, evaluate emerging technologies, and drive architecture decisions across product families.

Lead a Compliance Testing team for US Card, managing rapid response and control review testing, test calendar execution, technology-enabled testing transformation, stakeholder engagement, senior reporting, and audit/exam responses.

Develop and prepare multi-dimensional semiconductor device layouts from schematics, verify data integrity and design-rule compliance, lead major block developments, mentor junior designers, improve layout efficiency via automation/AI, and collaborate across global design, verification, and CAD teams to meet schedules and deliver quality layouts.

Lead architecture strategy and roadmaps for cloud-based, AI-enabled payment systems. Advise on technology selection, build reusable secure engineering patterns, develop and review production code, govern APIs and integration patterns, and drive digital transformation for onboarding and self-service experiences.

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.

Lead cybersecurity architecture for cloud-native enterprise solutions: evaluate controls and new technologies, advise stakeholders, provide technical guidance, promote firmwide SDLC practices, and mentor peers to mitigate risk and adopt strategic solutions.

Lead data ownership and governance for wholesale credit risk. Define data strategies, ensure data quality, metadata and lineage, enable data products, mitigate data risks, and coordinate cross-functional delivery for analytics and reporting.

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.

Lead second-line Compliance oversight for J.P. Morgan Wealth Management online brokerage and related products. Advise on regulatory compliance, identify and remediate conduct risks, manage compliance reviews, draft policies, support regulatory examinations, and partner with business, Legal, Risk, Technology and control functions globally.

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.

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.

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.

Define and drive vision, strategy, and roadmap for AI-powered merchant products using LLMs and agentic workflows. Size commercial opportunities, develop business cases, lead pilots through production, partner with engineering and data science, embed governance and responsible AI, and track product performance and adoption.

Support design, delivery, and commercialization of AI-powered payments products: manage roadmaps and backlogs, define requirements with engineering/design, run experiments and prompt/model evaluation, conduct market and user research, monitor product performance, and support launches and adoption.

Lead design and build agentic AI systems and production services, author secure high-quality code, create architecture artifacts, improve observability and testing, drive AI-assisted engineering adoption, and ensure privacy/security/compliance across end-to-end solutions.

Lead a portfolio of cloud-native full‑stack and SRE projects, mentor engineers, collaborate with product managers, and deliver resilient AWS/GCP/Azure services using Java, Python, containers, orchestration, and observability tooling.

Underwrite and assess multifamily loan packages prior to acquisition, evaluating property, sponsor, and market risks to determine supportable loan sizing. Work with internal and external partners to recommend lending decisions, document negotiated outcomes, and approve issuance. Enhance underwriting skills across diverse multifamily property types.

Participate in a two-day hackathon solving nonprofit data problems and network with Data & AI teams. Potential pathway to a 2027 Data & AI summer internship where you would build end-to-end data, analytics, and ML solutions, design data platforms and pipelines, develop production-ready models and dashboards, ensure data governance and compliance, work on agile teams, and deliver data-driven recommendations.

Design, build, and maintain secure cloud-based frameworks to host and deploy ML models using Python and AWS. Collaborate with data scientists and platform teams to productionize models, apply MLOps/LLMOps practices, use AI-assisted development tools, ensure CI/CD, resiliency, and operational stability, and contribute to engineering communities and architecture/design artifacts.

Lead a team delivering cloud-based, full‑stack enterprise platforms using distributed microservices. Collaborate with product managers, mentor engineers, experiment with new tech (including AI tooling), and build scalable solutions using languages like Java/Go/JavaScript and container orchestration on AWS and other cloud providers.

Lead and scale multiple AI-focused engineering teams to design, build, and deploy production-grade LLMs and generative AI solutions. Drive MLOps, low-latency inference microservices, CT/model lineage, and full-stack AI integrations with web and mobile frontends while partnering with product and data science.

Design and implement SystemVerilog RTL and microarchitectures for AI-optimized memory systems; perform synthesis and PPA analysis; document microarchitecture; evaluate tradeoffs and drive implementations from specification through silicon.

Lead Software Engineer responsible for designing, building, and maintaining scalable data pipelines and platform components (cataloging, quality, lineage, governance). Implements data modeling, partners with stakeholders to deliver production-grade code, automates operations, evaluates vendors, and leads Agentic Autonomous Lakehouse and engineering communities to drive platform innovation and operational stability.