Director, Enterprise AI Platform Architect

Position Summary

Vista Equity Partners is seeking a hands-on Enterprise AI Platform Architect to drive AI innovation across our 90+ portfolio companies. This role sits at the center of Vista’s Agentic Factory, our methodology for collaborating with portfolio companies to identify high-value agentic use cases and rapidly build production AI agents that deliver measurable business impact.

The ideal candidate combines deep technical expertise in generative AI, agents, and agentic architectures with the ability to move fast, shipping MVPs in compressed timelines and designing platforms that perform reliably in enterprise environments. You will work directly with portfolio company technology teams to design, implement, and scale AI solutions that enhance product offerings and drive competitive advantage.

This is a deep technical role regarding hands-on work alongside the portfolio engineering teams.

Responsibilities

Portfolio Company Collaboration & Agentic Delivery

• Partner with portfolio company technology and product teams to identify and prioritize agentic AI use cases aligned with their product roadmaps and business objectives.
• Lead end-to-end delivery of AI agent implementations using Vista’s Agentic Factory methodology, targeting MVP delivery in under a quarter.
• Run rapid proof-of-value sprints that demonstrate measurable business impact, then guide portfolio companies from prototype through production deployment.
• Lead AI maturity assessments across the portfolio using Vista’s scoring rubrics, identifying gaps and creating tailored improvement roadmaps.
• Conduct architectural reviews and provide recommendations for optimizing AI platform performance, scalability, and security.

AI Platform Architecture & Design

• Design scalable, resilient, and secure AI platforms leveraging public cloud AI services (AWS, Azure, GCP) while maintaining vendor independence through thoughtful abstraction layers.
• Develop and maintain reference architectures for AI applications, including generative AI models, agentic systems, and multi-agent collaboration patterns.
• Design appropriate autonomy levels for enterprise agent deployments, incorporating human-in-the-loop checkpoints calibrated to risk, regulatory requirements, and domain complexity.
• Define standards for AI model development, deployment, monitoring, and governance, including data privacy, model provenance, and audit trails for agent decision-making.

AI Innovation & Strategy

• Serve as a subject matter expert on generative AI, agents, and agentic architectures, providing thought leadership and strategic guidance to portfolio companies and Vista leadership.
• Identify and evaluate emerging AI technologies and trends, assessing their potential impact on portfolio company product roadmaps and Vista’s investment thesis.
• Develop and evangelize best practices for AI platform design, development, and deployment across the portfolio.

Due Diligence

• Assist in the due diligence process for potential portfolio companies, assessing AI technology capabilities, technical debt, and readiness for agentic AI adoption.
• Provide technical assessments that inform investment decisions and post-acquisition value creation plans.

Technical Expertise

• Generative AI including LLMs, diffusion models, and RAG architectures
• Agentic architectures, autonomous agents, and multi-agent systems
• Cloud AI platforms across AWS, Azure, and GCP
• AI model development, deployment, and lifecycle management
• Prompt engineering and model fine-tuning
• Machine learning and deep learning fundamentals
• Platform abstraction and vendor-independent architecture design

Operational Expertise

• Rapid proof-of-value delivery and compressed development timelines
• Cross-organizational collaboration and stakeholder management across multiple companies simultaneously
• AI maturity assessment and improvement planning
• Translating complex technical concepts for executive audiences
• Problem-solving and analytical thinking in ambiguous environments

Qualifications

 

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• 3+ years ofexperience in AI/ML platform architecture and development, with deep recent experience (2+ years) in generative AI and agentic architectures in production applications.
• Demonstrated track record of shipping AI applications to production environments, not just prototypes.
• Strong understanding of public cloud AI services and the ability to architect vendor-agnostic solutions with appropriate abstraction layers.
• Excellent communication, presentation, and interpersonal skills.
• Experience within private equity portfolio companies, consulting, or multi-client environments is a strong plus.

The annualized base pay range for this role is expected to be between $200,000 - $315,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant’s skill set. The base pay is just one component of the total compensation package for employees. Other components may include an annual cash bonus and a comprehensive benefits package.