EY - GDS Consulting - AIA - AI Platform Engineer- Senior

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Career Family       AIA – AI ENGINEER Role Type  Full Time     The opportunity We are seeking a dynamic Senior consultant to join our AI & Data Consulting team, focused on building scalable, enterprise-grade GenAI and Agentic AI solutions. The ideal candidate will bring a strong combination of AI engineering, platform development, cloud-native architecture, and backend engineering expertise, along with the ability to collaborate across cross-functional teams to deliver secure, scalable, and high-performing AI applications. You will work closely with data engineers, cloud architects, platform teams, security teams, product owners, and business stakeholders to design and implement LLM-powered platforms, agentic AI systems, Retrieval-Augmented Generation (RAG) solutions, and enterprise AI services that accelerate innovation and business transformation   Your key responsibilities Technical Excellence:    AI Engineering & Agentic AI Development

Design and develop enterprise-grade GenAI applications leveraging LLM frameworks such as LangChain, LangGraph / AutoGen / Google Agent SDK, and Model Context Protocol (MCP). Build and deploy agentic AI architectures, including multi-agent workflows, tool/function calling, enterprise integrations, and autonomous decision-making systems. Develop and maintain Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embeddings generation, vector indexing, retrieval optimization, and response grounding. Implement semantic search and knowledge retrieval solutions using vector databases such as Azure AI Search, Pinecone, FAISS, Redis Vector, and pgvector. Design robust AI system architectures that ensure scalability, reliability, security, and performance. Contribute to AI evaluation, observability, monitoring, and performance optimization of LLM-powered applications. Stay current with emerging trends in GenAI, Agentic AI, multimodal AI, enterprise AI platforms, and AI engineering practices.

Backend & Platform Engineering

Design and build scalable backend services using Python, FastAPI, REST APIs, microservices, and event-driven architectures. Develop reusable AI platform components, services, APIs, and integrations to accelerate enterprise AI adoption. Integrate AI solutions with enterprise systems, third-party applications, workflow platforms, and data services. Troubleshoot and optimize AI pipelines, APIs, vector stores, backend services, and cloud-native applications. Implement scalable deployment strategies using containerized and cloud-native architectures.

Cloud, Infrastructure & DevOps

Develop enterprise AI solutions using Azure OpenAI, Azure AI Services, and cloud-native services. Deploy and manage applications using Docker, Kubernetes, OpenShift, and container orchestration platforms. Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, and modern DevOps tooling. Ensure production readiness through monitoring, observability, automated testing, release management, and operational excellence. Support deployment and lifecycle management across development, testing, staging, and production environments.

AI Governance, Security & Responsible AI

Implement enterprise controls for PII protection, data privacy, AI security, compliance, and responsible AI practices. Support AI governance initiatives through monitoring, auditability, access controls, and compliance frameworks. Contribute to AI observability practices, including monitoring model behavior, hallucination risks, accuracy, latency, and retrieval quality. Ensure