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Vice President Theoretical Computer Science Jobs

Common Sense

Vice President, Engineering

San Francisco, CA · On-site

$175K - $205K/yr

Vice President, Engineering Common Sense Media is the leading nonprofit organization dedicated to ... Bachelor's degree in computer science, engineering, or a related field, or equivalent experience.

CLS-Group

Vice President, DevSecOps Lead

Iselin, NJ · Hybrid

$142K - $174K/yr

Functional title - Vice President, DevSecOps Lead * Department - Application Development ... Bachelor of Science in engineering or computer science is required Skills: * Ansible * Chef

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How much do vice president theoretical computer science jobs pay per year?

As of Jun 21, 2026, the average yearly pay for vice president theoretical computer science 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.
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VP, AI Strategy & Solutions

VP, AI Strategy & Solutions

Security Service Federal Credit Union

San Antonio, TX • On-site

Full-time

Posted 12 days ago

Job description

VP of AI Strategy & Solutions serves as the chief architect of our data-driven vision, demonstrating a deep understanding of strategic planning, our current AI models, and the multiple products of artificial intelligence that are most impactful to financial institutions. Reporting directly to the SVP, Enterprise Technology Solutions, you will be entrusted with developing, scaling, and continuously refining our AI strategy, ensuring it leverages our existing tools and technologies while aligning with organizational priorities and values. This role will be instrumental in transitioning our $14 billion institution toward a proactive, AI-integrated enterprise focused on high member engagement and operational excellence. The role strategically defines, establishes, and leads an AI-focused operating unit, providing strategic guidance on the AI roadmap, AI compliance, enterprise priorities, solution deployments, technical architectures, and the maturation of our data ecosystem. Leverages existing AI products, models and technologies-including but not limited to Generative AI, CoPilot Agent solutions, Robotic Process Automation, Machine Learning, predictive lending models, and intelligent fraud prevention systems-to drive measurable value for the credit union and its members. Creates and implements enterprise wide policies for ethical and secure AI use, ensuring all initiatives are contained, controlled, and in harmony with our brand reputation and risk tolerance. The VP maintains the ability to reassess and retract AI initiatives if they prove overly aggressive or misaligned with SSFCU's values, consistently safeguarding the integrity and trust of our institution.
AI Roadmap & Governance: Champions, designs and executes a multi-year AI strategy that prioritizes high-impact use cases (e.g., hyper-personalized member marketing, real-time fraud detection, and automated credit decisioning), Collaborates with internal departments and works within the credit union overarching AI Risk and Governance program. Establishes and enforces organization-wide policies for ethical and secure AI adoption, making sure all initiatives are controlled, well-contained, and reflect the credit union's risk tolerance.
Data Ecosystem Leadership: Oversees the modernization of data repository architectures, ensuring our data is secure, clean, accessible, and robust to fuel selected AI capabilities and solutions.
Operational Innovation: Partners with business unit leaders (e.g., Lending, Retail, Risk Management) to identify friction points that can be solved through automation and AI, driving a lower Efficiency Ratio across the organization.
Vendor & FinTech Integration: Evaluates and manages relationships with AI service providers and FinTech partners to accelerate our speed-to-market for valuable new intelligent solutions, functions and features.
Financial Services Expertise: 7+ years of leadership in Data Science, AI, or Digital Transformation within a regulated financial environment. Proven Track Record: Experience taking AI/ML models from a "proof of concept" to full-scale production in a multi-channel environment. Educational Foundation: MBA with a technical focus or an advanced degree in Data Science, Computer Science, Mathematics or a related field is preferred.

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