Overview
The Head of AI Practice leads the strategy, capability, and delivery of AI services across the organization.
This role builds the team, offerings, and partnerships that position the company as a leader in enterprise AI transformation.
Your Role and Responsibilities
What You’ll Do
Key Responsibilities
- Define and drive the AI practice strategy, offerings, and go-to-market.
- Build and mentor a high-performing team of AI engineers, architects, and consultants.
- Own delivery quality and outcomes across AI engagements.
- Develop partnerships with cloud and AI platform providers.
- Partner with sales to grow the AI pipeline and win strategic deals.
- Establish responsible AI standards, methodologies, and accelerators.
Represent the company as a thought leader in the AI space.
REQUIREMENTS
What This Role Requires
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or Business.
Experience
- 8+ years in technology, with 3+ years leading AI/ML or data teams and
practices. - Proven track record of building teams and delivering enterprise AI programs.
- Experience with commercial ownership (pipeline, P&L, or practice growth).
Technical Skills
- Strong understanding of the end-to-end AI landscape (GenAI, MLOps, data
platforms). - Familiarity with cloud AI ecosystems and partner programs.
- Ability to guide architecture and delivery decisions.
Soft Skills
- Visionary leadership and team building.
- Excellent executive communication and influence.
- Commercial and strategic acumen.
- Comfort operating in a fast-evolving market.
Working at Motivus
What Working Here Looks Like
- Guild community: You’re part of the [Data & AI / Backend / Cloud] Guild — a community of practitioners in your domain. Structured learning, peer review, and certifications happen here, not in isolation.
- Outcome accountability: Your work connects directly to a client result. We don’t measure activity — we measure delivery.
- AI in your workflow: Through AI Champions and Guild initiatives, you’ll actively use and shape how AI tools are applied to engineering work — not just hear about it in a townhall.
- Defined career path: Structured progression from individual contributor to technical lead to Guild leadership, with certifications and milestones that are visible, not arbitrary.
