EY’s Data & AI team within the AI Hub is seeking a Senior Consultant – AI Software Engineer in Dubai to rapidly deliver prototypes, proof-of-concepts (PoCs), minimum viable products (MVPs), and production-grade solutions that bring AI use cases to life. This role spans both front-end and back-end development, supporting the creation of dynamic AI-driven products such as GenAI-enabled web applications, use case marketplaces, and diagnostic tools for enterprise production environments.
About EY — Data & AI, AI Hub
Mission: Empowering clients to overcome accounting and financial reporting challenges through innovative technology
AI Hub Focus: Rapidly delivering prototypes, PoCs, MVPs, and production-grade AI solutions
Purpose-Driven: Building a better working world for people, clients, and communities
Culture: Outstanding leadership, teamwork, and a commitment to stakeholders
GenAI Innovation & Career Opportunity
Enterprise-Grade AI: Build GenAI-enabled web apps, use case marketplaces, and diagnostic tools
End-to-End Ownership: Design, build, and optimize scalable, secure, accessible web experiences
Cutting-Edge Stack: Work with RAG pipelines, vector databases, LLMs, and orchestration frameworks
Career Growth: Coaching, mentorship, and transformative leadership experiences within a global firm
Position Overview
This Senior Consultant – AI Software Engineer role demands expertise across both front-end and back-end development, translating business requirements into robust, scalable, secure, and accessible web experiences suitable for enterprise production environments. You will design end-to-end AI-driven solutions, build secure APIs, deploy production workloads on Microsoft Azure, and operate RAG pipelines that bring real AI use cases to life for EY’s clients.
Why This Role Matters: As Senior Consultant – AI Software Engineer at EY, you build GenAI products that drive real client value, work hands-on with RAG pipelines, vector databases, and LLM orchestration frameworks, deploy production workloads on Azure with AKS and Container Apps, collaborate across product, architecture, security, and cloud teams, and grow your career within EY’s global AI Hub.
Key Responsibilities
Full-Stack AI Product Development
- Design, build, and optimize end-to-end AI-driven web solutions
- Build secure, scalable, and maintainable APIs using Python and Node.js with FastAPI and Fastify
- Develop frontend experiences with TypeScript, React, and Next.js following enterprise UI and accessibility standards
- Translate business requirements into robust, scalable, and accessible web experiences
Cloud Deployment & DevOps
- Containerize, deploy, and operate applications in production using Docker and Kubernetes
- Design, implement, and maintain CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps
- Deploy and operate production workloads on Microsoft Azure, including AKS, Azure Container Apps, and Azure Container Registry
AI, RAG & Data Engineering
- Work with vector databases (Chroma, Milvus, Pinecone) and pgvector to build and operate RAG pipelines in production
- Work with LLMs and AI platforms such as Azure OpenAI, OpenAI APIs, or similar enterprise AI services
- Apply LLM orchestration frameworks such as LangChain or Semantic Kernel
- Manage relational databases (MS SQL Server, PostgreSQL) including schema design and query optimization
Engineering Excellence & Collaboration
- Apply SOLID principles, clean architecture, and enterprise design patterns
- Collaborate effectively with product, architecture, security, and cloud/platform teams
- Use AI coding assistants such as Claude Code or OpenAI Codex to accelerate delivery
- Contribute to architecture decisions, technical standards, and internal best practices
- Mentor junior engineers and contribute to engineering excellence initiatives
Qualifications & Requirements
Experience Requirements
- 5+ years of professional experience delivering enterprise-grade software solutions across backend and frontend systems
- Proven experience containerizing, deploying, and operating applications in production using Docker and Kubernetes
- Practical experience with vector databases and pgvector, building RAG pipelines in production
Essential Skills
- Strong hands-on experience with Python and Node.js using FastAPI and Fastify
- Solid frontend engineering experience with TypeScript, React, and Next.js
- Experience with CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps
- Hands-on experience with Microsoft Azure services including AKS and Azure Container Apps
- Experience with LLMs, Azure OpenAI, OpenAI APIs, and orchestration frameworks like LangChain or Semantic Kernel
- Strong documentation skills and experience contributing to architecture decisions
Nice to Have
- Exposure to MLOps or AI platform operations, including model lifecycle management and observability
- Experience with event-driven or distributed architecture (message queues, service buses, async processing)
- Knowledge of observability tools such as Azure Monitor, Application Insights, Prometheus, or Grafana
- Experience in regulated or compliance-driven environments such as financial services or audit
- Familiarity with infrastructure-as-code tools such as Terraform, Bicep, or ARM templates
About EY — Building a Better Working World
Join EY’s AI Hub, where teams rapidly deliver prototypes, PoCs, MVPs, and production-grade AI solutions that bring real-world use cases to life. EY empowers clients to overcome accounting and financial reporting challenges through innovative technology, offering competitive compensation, continuous learning, flexible work arrangements, coaching and mentorship, and a diverse, inclusive, and collaborative culture for those ready to shape their future.
Career Excellence: Build the GenAI products shaping the future of finance with a global professional services leader.
Who Should Apply?
- Full-Stack AI Engineers: With 5+ years building enterprise-grade Python and React applications
- RAG & LLM Specialists: Experienced with vector databases and LLM orchestration frameworks
- Cloud-Native Developers: Skilled in Docker, Kubernetes, and Azure deployment
- AI Product Builders: Comfortable with rapid prototyping and delivering client-centric MVPs
- Engineering Mentors: Experienced guiding junior engineers and shaping technical standards
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