Artificial Intelligence Jobs in Tempe, AZ

Lead enterprise AI strategy and architecture, guiding generative AI and ML adoption with governance, security, MLOps, and cross-functional enablement. Advise development teams, drive ROI, and ensure compliant, scalable AI solutions.

Lead a team to deliver AI/ML solutions, manage projects, ensure compliance, mentor staff, and collaborate with business stakeholders.

Develop and implement AI models and algorithms using Azure technologies, focusing on full-stack development, AI solutions, and collaboration with stakeholders to optimize business processes.

Support development and implementation of AI governance, security policies, and controls. Integrate security tools across AI platforms, document AI use cases, and design privacy/compliance frameworks. Collaborate cross-functionally with data, engineering, and compliance teams to ensure responsible, secure AI adoption.

Lead simulation-driven development of power modules using multiphysics (electrical, thermal, mechanical) models, digital twins, AI-augmented optimization, and automation to accelerate SiC/GaN power-electronics design and reliability prediction while collaborating with global teams.

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.

Lead and mentor AI engineers and data scientists to research, prototype, and productionize scalable AI/ML solutions (NLP, CV, predictive analytics, generative AI). Own MLOps, cloud integrations (Azure, AWS, GCP), ethical AI governance, model monitoring/versioning, and cross-functional deployment to meet business objectives.

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.

Join as a founding GTM team member to build and qualify pipeline, manage inbound chats/emails, run outreach automations, re-engage sign-ups, track CRM and metrics, and attend events to generate high-value relationships with developers, startups, and enterprises in the open AI ecosystem.

Lead design and implementation of identity and access controls for human and non-human (agentic) identities. Build runtime controls, secrets workflows, policy-as-code, monitoring, and governance for AI agents. Embed IAM into AI development, integrate telemetry with SIEM/SOC, ensure GRC compliance, and recruit and lead a team to scale NHI/agentic IAM capabilities.

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.

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.

Design, build, and maintain infrastructure and processes to govern and scale enterprise AI tooling. Integrate data feeds for usage and cost metrics, support LLM lifecycle management and benchmarking, implement AI governance guardrails, collaborate with architecture and cross-functional teams, and create enablement documentation.

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.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.