Shape your future with confidence at EY, a global leader committed to building a better working world. Join our AI-first EY.ai Center for Reimagination as a Technical Architect / Manager for AI Agentic Platform Engineering.

This role focuses on leading backend engineering for enterprise-grade digital and AI-native platforms, leveraging strong Python expertise and a working knowledge of Java and Go. You will define scalable architecture patterns for APIs, services, LLM integrations, and agentic frameworks. Your contribution will be crucial in translating AI concepts into scalable engineering patterns and client-ready solutions.

As part of EY's Global Delivery Services, you'll contribute to a worldwide network dedicated to supporting EY's growth agenda through exceptional client service and innovative solutions. We are a diverse team of over 80,000 professionals across ten countries, operating at the forefront of technology and client transformation.

Spearhead backend and agentic platform architecture for Python-led components, encompassing APIs, services, automation, AI/LLM integrations, and multi-agent workflows. Define critical design principles, reference patterns, and reusable engineering assets for backend teams.

Translate functional and non-functional requirements into robust architecture decisions focused on scalability, security, performance, and maintainability. Lead technical and code reviews, conduct dependency assessments, and ensure production readiness before releases.

Guide engineers on best practices for Python service design, Java service integration, API contracts, database interactions, and automated testing. Partner with product owners, architects, and security stakeholders to align technology with business objectives. Drive CI/CD adoption, environment readiness, observability, and release governance. Identify and mitigate delivery risks, remove technical blockers, and foster a culture of engineering excellence and documentation.

A strong hands-on background in Python and Java backend services, automation, and enterprise integration is essential. Proven experience designing REST APIs, microservices, and event-based integrations, alongside a solid understanding of SQL databases, data modeling, and transaction handling, is required.

Proficiency in CI/CD, Git, automated testing, code quality gates, and DevOps practices is a must. You should be adept at defining architecture decisions, documenting trade-offs, and governing implementation quality. A security-first mindset, including secure coding practices and vulnerability remediation, is crucial.

Mandatory experience includes AI engineering concepts, LLM solution design, prompt/orchestration patterns, and the safe integration of AI into enterprise applications. Hands-on knowledge of agentic frameworks like Microsoft Agent Framework, Azure AI Foundry, OpenAI Agents SDK, Semantic Kernel, AutoGen, LangChain, CrewAI, and LlamaIndex is expected, including autonomous workflow design and multi-agent orchestration. Understanding of robotics and automation platforms is also beneficial.