Data & AI Director

Valtech

20h•$200,000 - $250,000

About The Position

Valtech is hiring a Senior Director, Data & AI to help win and deliver complex client engagements across the Americas, particularly for industrial and manufacturing clients. This player-coach role combines client-billable technical leadership—typically across two engagements—with pursuit leadership, solution quality, staffing support, and development of reusable practice assets. The role reports to the VP and Head of Data & AI, Americas, and begins without direct reports, leading through influence and shaping how senior practitioners work. The position focuses on getting AI into production and keeping it there, with attention to the data, platform, evaluation, and operating foundations required for successful solutions. The director leads pursuits from qualification through signed statement of work, makes go/no-go decisions on pursuits they lead, and serves as technical lead on client engagements. They own architecture, technical risk, quality, and solution sign-off for the work they lead; advise clients on difficult technical tradeoffs; and help connect solutions to business outcomes. The director also coaches colleagues on pursuit quality, helps shape staffing, interviews senior technical candidates, and turns delivery experience into reusable reference architectures, estimating models, and solution patterns. They support the practice’s point of view and pursuits in industrial, manufacturing, agriculture, and distribution businesses, and help the practice adopt AI tools responsibly. This is a full-time position based in the United States, with remote and hybrid work options depending on country. The offered annual salary range is $200,000–$250,000, depending on experience and location.

Requirements

Typically 12 or more years of experience in data, analytics, and AI.
At least 5 years in consulting, professional services, or client-facing delivery roles, leading multiple engagements at once.
Hands-on depth in both AI and agentic solution design and modern data platform architecture; able to design in either area, lead technical teams in both, and engage effectively with client architects.
Deep, recent experience with at least one of Databricks, Google Cloud, or Microsoft data and AI platforms, and working fluency across the other two.
A track record of shaping and winning enterprise pursuits, including solutioning, estimating, scoping, and presenting to executive buyers.
Executive presence, with the ability to form and defend a clear point of view and revise it when evidence warrants.
Comfort working at a fast pace with shifting priorities and multiple clients requiring attention.
Experience delivering data or AI work for industrial, manufacturing, agriculture, or distribution businesses.

Nice To Haves

French language skills.
Current certifications from Databricks, Google Cloud, or Microsoft.
A public point of view on enterprise AI, such as published articles or conference talks.
Experience with Agile methodologies and consulting.

Responsibilities

Lead Data & AI pursuits from qualification through signed statement of work, including solution design, economics modeling, estimating, scoping, and executive presentations.
Make go/no-go decisions on the pursuits they lead based on value, risk, and delivery capability.
Turn broad client ambitions into phased programs that demonstrate value early and create a foundation for scale.
Improve the quality of colleagues’ pursuits through solution reviews and direct coaching.
Serve as technical lead on two client engagements at a time, owning architecture, technical risk, and quality.
Ensure AI solutions have the data, platform, evaluation, observability, and support foundations needed for production.
Act as a senior technical advisor to clients when difficult tradeoffs arise.
Own solution sign-off on the pursuits and engagements they lead.
Help shape staffing across data science, AI, data engineering, and platform work.
Partner with analytics, measurement, and optimization leaders to connect solutions to business outcomes.
Lead through influence and shape how senior practitioners across the practice work.
Interview candidates for data science, AI, data engineering, and platform roles, and help attract senior talent.
Develop reusable reference architectures, estimating models, and solution patterns based on delivery experience.
Support the practice’s point of view and pursuits in industrial, manufacturing, agriculture, and distribution businesses, in partnership with industry and client leaders.
Use AI tools in their own work and help the practice adopt them responsibly.