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Vice President Azure Ai information

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How much do vice president azure ai jobs pay per year?

As of Aug 25, 2026, the average yearly pay for vice president azure ai in the United States is $157,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $190,000.00 per year, depending on experience, location, and employer.

What does a Vice President Azure AI do?

A Vice President of Azure AI is a senior executive responsible for leading the strategy, development, and execution of artificial intelligence initiatives within Microsoft's Azure cloud platform. This role involves overseeing product development, managing large teams of engineers and researchers, collaborating with other business units, and driving innovation to support Azure's AI services. The VP ensures that Azure AI remains competitive, secure, and effective for customers across industries, while also aligning with the company’s overall vision and goals.

How does a Vice President Azure AI typically collaborate with cross-functional teams to drive AI initiatives within an organization?

A Vice President Azure AI often works closely with engineering, data science, product management, and executive leadership teams to define and execute AI strategies. This involves setting clear priorities, ensuring alignment between business goals and technical solutions, and facilitating communication across departments. The role requires a strong ability to translate complex AI concepts into actionable business plans while fostering a collaborative environment that encourages innovation and knowledge sharing. Regular meetings, strategic workshops, and joint project reviews are common practices to maintain alignment and track progress.

What are the key skills and qualifications needed to thrive as a Vice President Azure AI, and why are they important?

To thrive as a Vice President Azure AI, you need deep expertise in artificial intelligence, cloud computing, business strategy, and a proven track record in technology leadership, often supported by advanced degrees in computer science or related fields. Mastery of Azure AI services, data analytics platforms, and familiarity with industry certifications such as Microsoft Certified: Azure AI Engineer Associate are typically required. Exceptional leadership, communication, and strategic vision are crucial soft skills for driving cross-functional teams and fostering innovation. These skills are essential to effectively lead AI initiatives, align technology with business goals, and maintain a competitive edge in the rapidly evolving tech landscape.

What is the difference between Vice President Azure Ai vs Data Science Director?

AspectVice President Azure AiData Science Director
Required CredentialsAdvanced degrees in Computer Science, AI, or related fields; leadership experience; Azure certificationsMaster's or PhD in Data Science, Statistics, or related fields; strong technical background
Work EnvironmentExecutive leadership, strategic planning, cross-department collaboration, cloud platform managementTechnical team management, project oversight, data modeling, and analysis
Employer & Industry UsageTech companies, cloud service providers, large enterprises leveraging Azure AI solutionsResearch institutions, tech firms, enterprises focusing on data-driven decision making

The Vice President Azure Ai typically holds a strategic leadership role overseeing Azure AI initiatives at an executive level, while the Data Science Director focuses on managing data science teams and technical projects. Both roles require advanced technical knowledge, but the VP role emphasizes strategic planning and cloud platform oversight, whereas the Director role centers on technical execution and data analysis.

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Vice President Azure Ai jobs near you
Infographic showing various Vice President Azure Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $157,532 per year, or $75.7 per hour.

Vice President, Artificial Intelligence (VP of AI)

Las Vegas, NV

Credit One Bank
Finance and Insurance • 501 - 1,000 employees
Learn more about Credit One Bankexternal

Full-time

Re-posted 28 days ago

Job description

Position Summary

The Vice President of Artificial Intelligence (VP of AI) will lead enterprise-wide AI strategy, innovation, and execution. This role oversees the development, deployment, and governance of AI/ML systems across the organization, ensuring measurable business value, responsible AI practices, and alignment with corporate strategic goals. The VP of AI collaborates closely with Technology, Data, Operations, Risk, Compliance, and Business Unit leadership to build scalable AI platforms, optimize business processes, and accelerate digital transformation.

Essential Job Functions
  • Define and lead the enterprise AI strategy, including advanced analytics, machine learning, deep learning, and generative AI capabilities.
  • Build and oversee AI Centers of Excellence (CoE) to drive innovation, reusable solutions, and best practices.
  • Partner with IT, Data Engineering, and Cloud teams to establish a scalable AI/ML platform and MLOps frameworks.
  • Identify high-impact AI opportunities that drive automation, operational efficiency, customer experience improvements, and revenue growth.
  • Establish standards for Responsible AI, model governance, explainability, bias detection/mitigation, and regulatory compliance.
  • Lead the development, deployment, and lifecycle management of AI/ML models across multiple business units.
  • Oversee the creation of reusable AI components, annotation processes, model training pipelines, and evaluation frameworks.
  • Implement enterprise-wide generative AI solutions including LLMs, copilots, prompt engineering frameworks, and knowledge automation tools.
  • Collaborate with cybersecurity leaders to implement secure AI architectures, data protection controls, and model threat-defense mechanisms.
  • Promote cross-functional collaboration through transparency, communication, and evangelism of AI capabilities.
  • Build and manage high-performing AI teams including machine learning engineers, data scientists, AI product managers, and researchers.
  • Support annual planning, budgeting, strategic roadmaps, and executive-level presentations for AI programs.
  • Continuously monitor emerging AI trends, tools, and technologies and recommend adoption as appropriate.
  • Perform other duties as assigned.
Position Requirements
  • Bachelor’s degree in computer science, Engineering, Data Science, or related field. Master’s or PhD preferred.
  • 12–15+ years of progressive experience in AI/ML, software engineering, or data science, with 7+ years in leadership roles.
  • Demonstrated experience architecting, deploying, and scaling machine learning or deep learning systems in production.
  • Deep knowledge of Responsible AI frameworks, risk controls, and regulatory expectations.
  • Strong experience with cloud platforms (Azure preferred), distributed systems, and MLOps.
  • Exceptional communication skills, with ability to translate complex AI concepts for senior executives.
  • Proven ability to lead and inspire diverse technical teams.
  • Ability to drive outcomes, influence strategic decisions, and deliver business value.
  • Demonstrated alignment with company values of excellence, ownership, collaboration, and integrity.
PreferredCore AI Concepts and Technologies RequiredMachine Learning & Modeling
  • Supervised, unsupervised, reinforcement learning
  • Deep learning (CNNs, RNNs, Transformers)
  • Natural Language Processing (NLP) & LLMs
  • Generative AI (diffusion models, fine-tuning, RAG)
AI Engineering & MLOps
  • Model training, deployment, monitoring, and retraining
  • Feature stores, vector databases, and model registries
  • CI/CD pipelines for ML (MLOps)
  • GPU/accelerator compute architectures
Cloud & Infrastructure
  • Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
  • Kubernetes, containerization, microservices
  • Data platforms (Databricks, Snowflake, Synapse)
Responsible AI & Governance
  • Model explainability (SHAP, LIME)
  • Fairness, bias detection, model risk controls
  • Privacy-preserving ML techniques (differential privacy, federated learning)
Programming & Tooling
  • Python, PyTorch, TensorFlow, JAX
  • LangChain, semantic search, vector embeddings
  • Prompt engineering & LLM orchestration frameworks
Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.