Vice President - AI Consulting Engineering Lead

Role: Vice President - AI Consulting Engineering Lead NY/ NJ (preferred) / Remote Key Responsibilities: Lead Deep tech partner ecosystem and practice Collaborate with Labs and partner ecosystems (Google, Microsoft, Salesforce, UiPath, ServiceNow, AWS, Appian etc.) to integrate emerging capabilities into client solutions. Set up Deep tech labs with Nvidia, Open AI, Anthropic, Groq etc. Identify and incubate emerging technology use cases (e.g., Agentic, Quantum) relevant to client industries. Client Pursuit & Technical Solutioning Lead the technical pre-sales process, engaging directly with clients to understand business goals, pain points, and transformation needs. Develop end-to-end solution architectures across data platforms, cloud ecosystems (AWS, Azure, GCP), AI/ML, IoT, and other deep tech domains. Author and present compelling technical proposals, RFP/RFI responses, and solution blueprints that resonate with client stakeholders. Engage in RFP/RFI cycles and deal reviews to ensure technical integrity and differentiation. Transformation Consulting & Advisory Act as a strategic advisor to clients on digital transformation, data modernization, cloud migration, and emerging AI adoption. Assess current state architecture and co-create AI led transformation roadmaps aligned with future-state vision and business priorities. Lead client and internal architecture workshops Shape AI-first enterprise designs integrating data platforms, automation, and intelligent workflows. Partner with cross-functional teams across domain, tech, data, and AI to define solutions for large transformation deals. Translate business objectives into executable technology roadmaps with clear ROI and scalability. Define architectural guardrails, reusable components, and accelerators for repeatable deployment patterns. Mentor solution and engineering teams to adopt modern design principles Qualifications: 15+ years in enterprise architecture, engineering, or solution leadership within consulting, SI, or digital practices. Proven experience in architecting data-driven, AI-enabled enterprise platforms. Understanding of cloud-native architectures, integration frameworks, data fabric/mesh, and AI orchestration. Stakeholder management and executive communication skills.