EY - GDS Consulting - AIA - Full stack engineer - Manager

Opportunity

AI leadership and delivery

• Lead enterprise AI, GenAI, agentic AI, and RAG solution design and delivery aligned with business goals.
• Define AI strategy, roadmaps, governance frameworks, and operating models for enterprise adoption.
• Drive architecture and implementation of AI platforms, copilots, multi-agent systems, conversational AI, and intelligent automation.
• Identify valuable use cases, define success measures, and realize business value with stakeholders.
• Oversee the lifecycle from ideation through architecture, development, deployment, monitoring, adoption, and improvement.
• Lead and mentor cross-functional teams of AI engineers, data scientists, architects, and developers.

Governance and practice development

• Establish Responsible AI, security, privacy, compliance, and risk management practices.
• Define evaluation frameworks, quality standards, and performance metrics; guide RAG, knowledge management, and agentic workflows.
• Manage stakeholder communication, executive reporting, budgets, resource planning, and delivery governance.
• Build reusable accelerators, reference architectures, and AI practice capabilities; track emerging AI trends.

Experience and education

• 10+ years overall experience, including 5+ years leading enterprise AI/ML, GenAI, or data-driven transformation initiatives.
• Production-grade enterprise AI delivery and scaling experience from concept through deployment and adoption.
• Experience leading cross-functional AI, architecture, data science, and development teams.
• Bachelor's, master's, or PhD in computer science, data science, engineering, or a related field.

Technical skills

• Strong knowledge of LLMs, GenAI, agentic AI, multi-agent systems, RAG, copilots, conversational AI, and AI agents.
• Experience with enterprise AI platforms such as Azure AI Foundry, Azure OpenAI, Databricks, vector databases, and enterprise search.
• Knowledge of AI evaluation, guardrails, observability, Responsible AI, security, privacy, compliance, and risk management.
• Experience with prompt engineering, agent orchestration, tool integration, workflow automation, MLOps, and LLMOps.
• Strong analytical, problem-solving, strategic thinking, stakeholder management, and communication skills.

Application guidance

• Be prepared to discuss at least two AI/GenAI implementations, including business use case, personal contribution, technical approach, and measurable outcomes.

Benefits and culture

• EY describes learning and development, flexible ways to make an impact, leadership support, and an inclusive culture.