VP - AI Solutions Engineering

About the Company:

ANSR partners with the world's leading enterprises to design, build, manage, and operate Global Capability Centers (GCCs) that power global growth. As the market leader in GCC transformation, ANSR has established 200+ centers worldwide, hiring over 200,000 professionals, managing 12 million sq. ft. of enterprise workspace, and enabling $2.2B+ in cumulative investments.

Our end-to-end solutions simplify global expansion by seamlessly integrating talent, HR, workspace, technology, and compliance across the world's premier talent hubs. By combining deep operational expertise with technology-led innovation, we help enterprises scale with speed, precision, and confidence.

At the heart of our ecosystem is 1Wrk, our AI-powered global work platform that unifies people, processes, and infrastructure into one cohesive operating model, empowering organizations to access world-class talent and drive sustainable, long-term success.

Backed by Accenture, Accel Partners, and ServiceNow, ANSR blends technological innovation with operational excellence to help enterprises build their global future.

Visit www.ansr.com to learn more.

Job Summary:

We are building our AI Solutions Engineering practice and looking for a senior leader to define, architect, and scale enterprise AI agent deployments for global clients. This role sits at the intersection of consulting, engineering, and AI transformation, with responsibility for shaping how AI solutions are designed, integrated, and operationalized inside complex enterprise environments.

The ideal candidate brings a strong combination of enterprise AI architecture expertise, client engagement capability, and builder mindset. This individual will work closely with consulting and business leaders to define AI solution strategy, evaluate technology ecosystems, lead technical implementation, and build scalable AI engineering capabilities from the ground up.

This role requires someone who can engage confidently with both technical teams and senior business stakeholders, translating AI capabilities into measurable business outcomes and operational value.

Key Responsibilities:

AI Solutions & Platform Engineering

• Define the technical vision and architecture for enterprise AI agent platforms and AI-enabled solutions.
• Design scalable AI solution frameworks integrating proprietary platforms, partner technologies, and enterprise systems.
• Lead end-to-end deployment of AI agents and automation solutions within client environments.
• Evaluate build vs. buy decisions across AI tools, frameworks, and ecosystem partners.
• Establish engineering standards, governance models, and deployment best practices for enterprise AI solutions.

Client & Business Engagement

• Partner with client CXOs, business leaders, and consulting teams to identify AI transformation opportunities.
• Translate complex technical concepts into business outcomes, ROI, efficiency gains, and operational impact.
• Support client presentations, workshops, solution demonstrations, and strategic advisory conversations.
• Act as a trusted advisor during AI transformation initiatives and enterprise modernization programs

Cross-Functional Collaboration

• Work closely with consulting, product, data science, cloud, and delivery teams to ensure seamless execution.
• Collaborate with external partners, hyperscalers, and AI platform providers to strengthen ecosystem capabilities.
• Ensure AI deployments align with enterprise security, compliance, governance, and scalability requirements.

Experience:

• 8 -15 years of experience in enterprise technology, AI/ML engineering, or platform architecture.
• Proven experience designing and deploying enterprise AI/LLM-based solutions at scale.
• Strong experience working with cloud ecosystems such as AWS, Azure, or GCP.
• Experience leading technical teams and building engineering capabilities from scratch.
• Strong stakeholder management and executive communication skills.
• Ability to articulate AI business value to non-technical audiences including CFOs, COOs, and business leaders.
• Experience in consulting, pre-sales engineering, or client-facing transformation roles.
• Exposure to AI agents, GenAI platforms, orchestration frameworks, and enterprise automation.
• Experience working with external clients, partners, or enterprise advisory engagements.
• Background in scaling AI transformation initiatives across multiple business functions.