Artificial Intelligence Jobs in Tempe, AZ

Lead identification, design, and implementation of scalable automation and AI solutions. Collaborate with business, operations, and technical teams, run solution workshops, define integrations and infrastructure needs, validate designs as a Power Platform maker, and drive governance, adoption, and cross-functional delivery.

Lead and scale advanced manufacturing operations, owning safety, quality, delivery, cost, and customer satisfaction. Drive operational transformation through automation, digital manufacturing, AI/analytics, and continuous improvement. Oversee supplier quality, materials qualification, production planning, and workforce development while partnering cross-functionally to support capacity expansion and business growth.

Lead architecture and technical strategy for an agentic AI claims automation platform. Define end-to-end architecture, enable multi-agent workflows, integrate models and MLOps, ensure governance, resilience, observability, and cost efficiency, and mentor architects while aligning with enterprise AI standards.

Design, build, and operate petabyte-scale data pipelines for AI training and evaluation. Responsibilities include ingestion across modalities, cleaning, deduplication, dataset versioning and lineage, high-throughput data loading for accelerator training, labeling and human-in-the-loop workflows, storage architecture, data privacy and contamination controls, observability of data quality, and cross-functional collaboration with ML researchers to optimize model training efficiency and cost.

Lead design and governance of LLM-based application architectures, prompt and agent patterns, RAG pipelines, evaluation frameworks, and developer tooling. Ensure safety and robustness through guardrails, red-teaming, and optimization of latency, cost, and quality while mentoring teams and translating LLM research into production-ready solutions.

Design, optimize, and deploy ML models for resource-constrained edge devices. Apply compression, quantization, and hardware-aware tuning; build cross-platform inference runtimes; ensure secure, privacy-preserving on-device workflows; collaborate with hardware/firmware teams; develop benchmarking, telemetry, staged rollout, and documentation for production edge AI.

Senior enterprise technology leader to define and execute ASUs AI-ready data ecosystem, enterprise integration, and intelligent platform architecture. Lead AI/ML platform strategy, semantic analytics, cloud-native infrastructure, responsible AI governance, and organizational transformation to scale AI-enabled student success, research acceleration, and institutional operations.

Lead IAM architecture for AI workloads and conversational agents: design and validate OAuth/OIDC patterns, build POCs, integrate IAM with gateways, agent runtimes, and CI/CD/IaC, define lifecycle and governance, troubleshoot identity flows, ensure compliance, and transition patterns to production while mentoring teams.

As AI Resilience Fund Manager, you will create and manage a fund focused on resilient investments amidst AI disruptions and economic shifts, developing the investment thesis and strategy, leading fundraising, and advising investors over a 20-year horizon.

Lead and develop a high-performing engineering team for software solutions in AI and cloud technologies. Oversee delivery, security compliance, and operational excellence while mentoring talent and driving innovation.

Design, build, and deploy ML models and end-to-end pipelines; implement MLOps practices; deploy containers to cloud production; monitor model performance and drift; collaborate with engineers and product teams; optimize latency and throughput; write production-quality code and mentor junior engineers.

Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Build internal AI-powered applications for Solutions Engineering, Sales, and Marketing: prototype with AI-native tools, integrate APIs and cloud services, deploy and maintain production products, and drive adoption and continuous improvement.

Lead AI/ML product management for strategic, cross-divisional products. Define features, implementation plans, and market analysis; drive CI/CD, automated deployment, and UX improvements. Coach technical teams, influence stakeholders, and align business outcomes to product strategy.

Build, deploy, and maintain internal AI-powered applications and orchestration pipelines. Re-engineer business workflows for automation, define standards for reliability and observability, collaborate with IT/Security/DevOps, and mentor team members to drive company-wide AI adoption and measurable efficiency gains.

Design, build, fine-tune, evaluate, and deploy production-grade ML and LLM systems. Implement transformer models, RAG architectures, and agentic workflows; develop MLOps pipelines, containerized deployments, monitoring, and AI evaluation frameworks; collaborate cross-functionally and provide technical leadership and mentorship.

Lead vision, strategy, and delivery of AI-driven solutions across mortgage and home equity origination. Define roadmaps, build business cases, select vendors, and ensure model governance, compliance, and integration. Partner with data science, engineering, operations, risk, and stakeholders to launch AI capabilities, measure outcomes, drive adoption, and optimize product performance.

Lead a small team to design end-to-end solution architectures for complex PBM initiatives. Ensure adherence to architecture principles, drive modernization, lead PoCs and technology deep-dives, advise App Dev on performance and technical roadblocks, and integrate APIs, microservices, cloud, streaming, and AI/ML automation into solutions.

The AI Engineer will develop user-facing features using TypeScript and React, collaborate on product ideas, and leverage AI coding tools in a high-velocity team environment.

The Strategic Finance Manager will oversee financial forecasting, develop reporting packages, and enhance financial models while collaborating with executive teams on financial performance insights.

As a Product Manager, you will work closely with engineering, collecting user feedback, prototyping ideas, and balancing user needs with technical constraints in AI-driven developer tools.

Senior technical subject-matter expert responsible for Security Posture Management: define operating model, lead initiatives, assess and design controls, monitor KPIs/KRIs, report risks, drive remediation, and advise cross-functional teams to ensure compliance with regulatory and security frameworks.

Designs, develops, and deploys AI-powered solutions in the Salesforce ecosystem. Builds Agentforce agents, Agent Actions, prompt templates, RAG grounding, Apex, LWCs, Flows, integrations, and CI/CD to automate coaching workflows and personalized student engagement while ensuring governance and monitoring.

Research, design, and implement foundation models for machine-generated and graph data; develop distributed training and inference pipelines; collaborate with engineering and product teams to productionize models; evaluate new AI/ML techniques and drive MLOps, monitoring, and model optimization to improve scalability and reliability.