Qvest.Us3mo ago

Practice Lead, Applied AI

United States·Los AngelesFull-timelead

Data ScienceOtherApplied AiPractice Lead

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Overview

Who We Are Qvest US is the global leader in technology and business consulting for the Media & Entertainment and Consumer Packaged Goods & Retail industries. We strategize, advise, design,

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Qvest US is the global leader in technology and business consulting for the Media & Entertainment and Consumer Packaged Goods & Retail industries. We strategize, advise, design, develop and implement future-forward business & technology solutions. With expertise in digital media supply chain, data & analytics, IP & rights management, broadcast transformation, Salesforce and applied AI, our exceptionally talented teams partner with Fortune 1,000 companies to revolutionize markets and set new industry standards.

Qvest US is seeking an experienced leader to oversee our US Applied AI practice. You will be responsible for leading the Applied AI practice including strategy, business development, team development and project delivery. This includes leading interactions with customers and channel partners, as well as internal stakeholders to promote the Qvest Applied AI practice and actively participate in the growth of Qvest.

The Practice Lead will execute a 2026 GTM (go-to-market), updating as necessary, and create subsequent GTM strategies for the Applied AI practice. They will work closely across Practices, Business Units, and Sales & Marketing to communicate strategy, offerings, and innovation within the Practice, identifying opportunities for new and existing services and solutions that can be offered to clients. The role will also be responsible for working closely with clients in identifying their business needs and providing technical solutions.

You will provide operational management on a daily, weekly, and monthly basis to ensure that the Applied AI business is organized and executed so as to positively impact Qvest revenue, retention, growth, and customer satisfaction.

Our clients are looking for our expertise to help them build modern AI solutions. We work closely with clients to understand their IT infrastructure, data estate, business objectives, and how Applied AI solutions can help them achieve those objectives. Our industry focus is the Media & Entertainment industry.

Refine/update a 2026 and beyond go-to-market strategy that resonates with the Media and Entertainment industry and optimizes company growth.

Be accountable for the Applied AI practice revenue and budgets for each year and help create them for following years

Partner with vendors, leadership and sales to identify customer opportunities or identify them using other means. Once identified, understand business objectives and challenges, establish trust and set vision with the customer, develop proposals, and win work for the practice

Be the face of the practice, develop the practice’s internal and external presence, evangelize and champion our services and products

Articulate the value proposition and ROI of our services and proposed solutions to prospective customers

Stay abreast of industry and technology changes, in the areas of Applied AI technologies, including foundation models and generative AI, especially as they lead us into a world that continues to rapidly move towards AI solutions.

Cultivate and manage the portfolio of offerings, SOWs, and IP to maximize profitability and achieve revenue/margin objectives

Manage the day-to-day operations of the team, including resource allocation, budgeting, and manage a practice-level profit and loss statement, including project management as needed

Contribute to internal growth initiatives including mentorship, recruitment, strategy and/or methodology enhancement

Oversee and ensure accuracy of project plans and estimates during the sales process.

Monitor active projects, ensuring priorities, issues, and risks are appropriately managed.

Follow consulting methodology, lead & advise project teams through all core project phases, including project setup, requirements gathering, design, development, testing, and deployment

Ensure client satisfaction and maintain executive level relationships through consistent support, impactful thought leadership and high-quality project execution.

Understand, develop and articulate complex business challenges into actionable plans with clear and concise communication

Facilitate workshops, provide status updates, and lead meetings across the executive levels of client organizations

Leadership experience managing teams of functional and technical resources

Hands-on AI expertise and experience including but not limited to:

8+ years in consulting or AI-focused roles, with experience working across modern machine learning and AI platforms and tools and guiding teams delivering both classical ML and generative AI solutions.

Strong understanding of designing and delivering AI solutions on cloud platforms (AWS, Azure, or GCP), including collaborating with engineering teams, and operational considerations such as scalability, governance, and cost.

Experience leading the delivery of business-driven AI initiatives, translating client business challenges into practical, scalable AI use cases

An understanding of current key AI trends and the AI landscape

Passion for and proven experience with consulting business development

Eagerness to help build and lead a best-in-class Applied AI Practice

Experience with project planning, including tasks, budgeting, resource allocation and balancing

A track record of highly impactful work at prior companies, including both as a manager, a manager of managers, and as an individual contributor.

Media & entertainment or adjacent industry experience

Knowledge of industry best practices in Applied AI

Experience at a large consulting firm (e.g., Accenture, Deloitte, EY, CapGemini, PWC)

Bachelor’s degree in engineering, computer science, data science, information systems, or a related quantitative field (advanced degree a plus).

Familiarity with established and emerging AI technologies, including foundation models, generative AI, MLOps tooling, model governance, and responsible AI practices.