AI Practice Delivery Lead (Senior Manager) / Technology Consulting

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The opportunity

EY DnA is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors.

We implement information-driven strategies, data platforms and advanced data analytics solution systems that help grow, optimize and protect client organizations. We go beyond strategy and provide end to end design, build and implementation of real-life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region.

We are seeking an AI Practice Delivery Lead (Senior Manager) to spearhead our advanced AI engineering practice in a consulting and professional services context. This role is a senior leadership position with end-to-end accountability for client success and practice growth. You will oversee multi-project delivery, shape solution architectures, and ensure technical excellence while also driving sales, go-to-market (GTM) strategy, and P&L management for the AI practice. As a thought leader at the forefront of AI (LLMs, generative AI, knowledge systems, etc.), you will engage C-level client stakeholders across APAC and globally, design transformative AI strategies, and lead teams to implement state-of-the-art AI solutions (LLM-based platforms, intelligent automation, knowledge-driven systems) across industries. This position combines strategic leadership with deep technical credibility to scale AI-driven innovation for our clients and our firm.

Your Key Responsibilities

Practice & Delivery Leadership: Oversee the end-to-end delivery of multiple concurrent AI engagements, ensuring projects meet or exceed client expectations in impact, timeline, and quality. Act as Solution Architect and final technical authority, guiding design of complex AI systems (enterprise LLM applications, CV/NLP/analytics solutions, etc.) and ensuring robust, scalable architectures. Establish and enforce best practices, delivery methodologies, and governance standards across the AI engineering practice.
Sales & Business Development: Drive go-to-market and sales efforts for AI engineering services. Partner with account teams to identify and pursue new business opportunities, shape value propositions, and lead client proposals and pitches. Own the development of compelling use-cases, demos, and prototypes that showcase our AI capabilities (e.g., generative AI assistants, vector database-driven search solutions, industry-specific AI accelerators). Take accountability for achieving sales targets and expanding the project pipeline.
P&L and Practice Management: Serve as the P&L owner for the AI engineering practice or portfolio. Develop business plans and pricing strategies for engagements, managing resource allocation, utilization, and profitability. Monitor financial performance and implement measures to improve margins and delivery efficiency (e.g., optimizing reuse of assets, balancing onshore/offshore mix, efficient GPU resource management to control cloud costs).
Client Advisory & Relationship Management: Act as a trusted advisor to senior client executives, helping shape their AI strategy and roadmap. Conduct strategic workshops and assessments to identify high-impact AI opportunities. Ensure strong client relationships and satisfaction by regularly engaging sponsors, providing thought leadership, and swiftly addressing any delivery issues or scope changes. Liaise between clients and technical teams to keep solutions aligned with business goals and industry regulations.
Technical Innovation & Enablement: Stay at the cutting-edge of AI advancements (e.g., new LLM releases, open-source AI frameworks, emerging tools for knowledge graph construction, etc.) and infuse these into our offerings. Guide teams in implementing specialized techniques like model fine-tuning, reinforcement learning, RAG and semantic search architectures, or ontologies where relevant to client problems. Champion responsible AI and ensure solutions meet security, compliance, and ethical standards. Promote innovation by incubating new accelerators, reusable components, and partnerships with technology vendors and AI research communities.
Team Development & Cross-functional Leadership: Build and grow a high-performing AI engineering team. Mentor managers and senior engineers, fostering a culture of continuous learning and excellence. Recruit top talent and upskill existing team members in advanced AI technologies (e.g., LLMOps, GPU optimization, vector databases). Collaborate closely with other practice leaders (Data, Cloud, Industry SMEs) to deliver integrated solutions. Contribute to internal knowledge sharing, case studies, and thought leadership publications to elevate the firm’s reputation in AI.

To qualify for the role, you must have

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or similar. MBA or other relevant postgraduate degree is advantageous, especially to underscore business management capabilities.
Relevant certifications (cloud architecture, data science, project management) or evidence of ongoing professional development in advanced AI domains will strengthen candidacy
12+ years of experience in advanced analytics, AI engineering, or related technology fields, with at least 3–5 years in a consulting leadership role.
Proven track record of leading large-scale AI solution implementations for enterprise clients and managing multi-million dollar progr