Execute work and present its findings to the client and their stakeholders
Anticipate and identify risks and escalate issues as appropriate
Work closely with colleagues, determine whether the work plan is properly executed, documented and concluded in compliance with Quality & Risk Management guidelines
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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.
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