AI Practice Manager

GSPANN is hiring an AI Practice Manager to lead AI strategy, build governance frameworks, and drive client engagements and team growth.

• Lead capability demonstrations for clients as the primary spokesperson for solutions and applications in development, serving as the main point of contact.
• Drive AI practice strategy, including offerings, go-to-market (GTM) approach, and capability roadmap.
• Build an AI Center of Excellence (CoE) and governance frameworks, ensuring quality and delivery excellence across AI projects.
• Develop reusable AI accelerators, frameworks, and best practices in collaboration with subject matter experts (SMEs) such as architects and development leads, establishing shared benchmarks for the practice.
• Support the team with guidance on domain-specific aspects.
• Drive AI adoption initiatives across the organization by delivering webinars, training sessions, and thought leadership content to enable teams.
• Ensure the AI practice stays aligned with emerging technologies by continuously monitoring industry trends.
• Drive pre-sales, solutioning, and client engagements.
• Lead proposals for assigned clients, covering presentations, scoping, and effort estimation.
• Develop statements of work (SOWs) with milestone plans, key deliverables, assumptions, commercial terms, dependencies, and other contractual artifacts.
• Manage change requests and scope creep.
• Ensure project baselines are tracked so activities progress as planned.
• Manage profit and loss (P&L) for projects, ensuring margins and client service level agreements (SLAs) are consistently met.
• Implement strategies to mitigate shortfalls in timeline and budget.
• Ensure the team maintains a high level of competence and operational excellence.
• Manage status reporting, publishing metrics-based updates for internal and external stakeholders.
• Drive proactive risk identification across programs and projects, developing mitigation plans.
• Collaborate with the sales team to identify new service opportunities within existing accounts and support deal closure.
• Build thought leadership by identifying business problems and creating solutions and frameworks that can be offered to clients and monetized, including whitepapers, blogs, and points of view (POVs).
• Develop and scale AI competencies across teams through onboarding, training, knowledge transfer (KT), skill-building plans, hiring, and certifications.
• Support team members through mentorship and motivation.
• Manage employee engagement, including appraisals and retention.

• Bring 20+ years of overall experience, including 8+ years in leadership roles.
• Demonstrate strong experience in AI and GenAI solutioning and enterprise architecture.
• Develop AI use cases into reusable products and accelerators.
• Apply programming skills in languages and frameworks such as Java, Spring Boot, and Python.
• Work with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
• Utilize Azure OpenAI, AWS Bedrock, and GCP Vertex AI for enterprise AI solutions.
• Develop AI agents and agentic workflows.
• Utilize frameworks such as LangChain and Semantic Kernel, or similar tools.
• Apply AI assistants such as Claude, Copilot, and Cursor to accelerate delivery.
• Manage large-scale, multi-site, multi-brand, multi-country eCommerce implementations.
• Bring experience in B2B and B2C implementations.
• Work with eCommerce platforms including Salesforce Commerce Cloud (SFCC, formerly Demandware), Hybris, and Magento.
• Demonstrate knowledge of Product Information Management (PIM), Digital Asset Management (DAM), Content Management System (CMS), Loyalty, and Order Management System (OMS) platforms connected to eCommerce.
• Apply a deep understanding of eCommerce flows and integrations with internal and third-party systems.
• Utilize AI-driven solutions to enhance business return on investment (ROI).
• Apply AI capabilities to deliver end-to-end solutions.
• Manage large teams and practices, including accounts of up to approximately 100 resources across single or multiple engagements.
• Demonstrate excellent understanding of industry-proven design patterns and strong problem-solving skills.
• Apply pre-sales expertise in end-to-end solution architecture, covering technical and deployment design along with non-functional and performance considerations, and in developing proposals for requests for proposal (RFP) and requests for information (RFI).
• Demonstrate strong knowledge of AI platforms and enterprise ecosystems.
• Bring excellent leadership, communication, and stakeholder management skills.
• Demonstrate strong understanding of key performance indicators (KPIs) that measure and demonstrate productivity improvements.
• Utilize estimation techniques such as use case points, function points (FP), and story points.
• Demonstrate strong presentation and demo skills for engaging customers and internal management.
• Bring experience driving organizational initiatives such as case studies, white papers, and blogs.