Associate Director, AI & Engineering Ops

Vista Equity Partners Management

13d•$160,000 - $215,000•Remote

About The Position

We are looking for an Associate Director to join Vista’s Value Creation Team (VCT) in the Product and Technology (P&T) Practice, which serves as a trusted advisor to portfolio company leaders in product, technology and cybersecurity. As an Associate Director focused on AI & Engineering Operationsand working with engineering leaders across our enterprise software portfolio companies, you will: Work with VCT colleagues, investment team members, and portfolio company executives on value creation initiatives that drive AI & Engineering Operations transformation and adoption Define and implement AI & Engineering Operationsbest practices across the portfolio, including code generation tool deployment, AI-assisted QA strategies, and SDLC optimization with AI Lead portfolio companies through AI & Engineering Operations maturity assessments and create roadmaps for AI adoption across the entire development lifecycle This role will give exposure to investment decision making, value creation and transformation and will help you gain practical experience scaling the world’s premier software/technology businesses. Former members of this team have gone on to accelerate their careers in larger leadership roles within Vista and joined companies in the Vista portfolio as engineering leaders. The role is based in San Francisco, CA, Austin, TX, or remote locations and is available for an immediate start. We support flexible ways of working, but believe the best collaboration happens at least partly in person. Some travel required.

Requirements

Passion and curiosity for technology, software and data, as well as what makes successful technology companies and investors
7+ years of experience in engineering leadership, DevOps, or engineering operations roles, with at least 2 years focused on AI tool usage, adoption and implementation
Hands-on experience implementing and measuring success of AI code generation tools at scale
Deep understanding of engineering metrics platforms and ability to translate data into actionable insights
Proven track record of successfully rolling out new engineering tools and processes across multiple teams or organizations
Experience managing vendor relationships and evaluating emerging technology solutions
Strong technical background with ability to understand and discuss architectural implications of AI tool adoption including usage of rules and instructions files
Experience with change management and driving adoption of new technologies in engineering organizations
Knowledge of compliance and security considerations for AI tool usage in enterprise environments
Willingness to travel up to 25% of time
Strong communication and project management skills
Excellent analytical and problem-solving skills, both in individual and collaborative environments
Ability to drive cross-functional analysis, integrating perspectives on technology, business and finance
Ability to bring structure to large, complex questions with limited guidance
Ability to multi-task, operate independently, and deliver on tight deadlines

Nice To Haves

Computer Science or technology-related degree from a top undergraduate institution

Responsibilities

Partner with portfolio company executives to develop AI & Engineering Operations strategies that accelerate development velocity and improve code quality through AI adoption
Assess and implement AI-powered development tools across portfolio companies, including code generation platforms, establishing metrics for adoption rates, productivity gains, and ROI
Build and maintain strategic relationships with leading AI tool vendors (GitHub Copilot, Claude Code, Cursor, Cognition, etc.) and model providers (Anthropic, OpenAI) to secure favorable terms and early access to new capabilities
Develop deep expertise in AI code generation tools, including configuration best practices, rollout strategies, and methods for tracking effectiveness and developer satisfaction
Design and implement engineering metrics programs using platforms like Jellyfish, LinearB and DX, establishing KPIs that matter, creating action plans when metrics indicate issues and creating mechanisms to measure AI engineering impact at scale
Create scalable AI & Engineering Operations playbooks tailored to different organization sizes and maturity levels
Identify and pilot emerging AI technologies across the SDLC including AI-assisted testing, documentation generation, code review automation, bug backlog remediation and predictive analytics for development
Lead the portfolio's thought leadership in AI & Engineering Operations, staying ahead of trends and establishing Vista companies as early adopters of proven technologies
Collaborate with portfolio company executives, investment teams and operating partners to develop and shape the value creation strategy to achieve the Investment Thesis

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