DE - AE- AI Architect-SM-GDS04
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Architecture
- Posted
Skills
Must have
- Education: BE/BTech/MCA or equivalent degree in computer science, engineering or a related discipline.
- Overall experience: 15+ years in software architecture, engineering and enterprise solution delivery.
- Java/J2EE depth: 8+ years designing and delivering enterprise-grade Java/J2EE applications, with strong Spring ecosystem experience.
- Architecture depth: 5+ years in microservices, distributed systems, API-led and event-driven architecture.
- AI delivery: 2+ years of hands-on architecture and implementation experience in AI/ML/GenAI initiatives, with evidence of production or enterprise-scale delivery.
- Leadership: Experience leading multidisciplinary engineering teams and owning architecture and delivery outcomes.
- Consulting: Strong client engagement, workshop facilitation, presales, storytelling and senior stakeholder communication skills.
Nice to have
- Python and AI service development using FastAPI or Flask, alongside the primary Java/J2EE engineering background.
- Fine-tuning concepts, model optimization, quantization, open-source models and multimodal AI.
- GraphRAG, Knowledge-Augmented Generation, enterprise knowledge platforms and advanced retrieval/evaluation patterns.
- Workflow orchestration or BPM platforms such as Camunda, Airflow or Prefect.
- Infrastructure as Code and platform engineering using tools such as Terraform and GitHub Actions or Azure DevOps.
- Experience across regulated industries and familiarity with enterprise privacy, security and compliance expectations.
- Relevant cloud, architecture, Java or AI certifications; contributions to internal accelerators, open-source projects or technical communities.
Full description
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.
Senior AI ArchitectExperience
- 15+ years overall; 8+ years in Java/J2EE; 2+ years in AI/GenAI delivery
Role focus
- AI-led modernization of enterprise Java platforms and creation of scalable, secure AI solutions
The opportunity
We are seeking a Senior AI Architect who combines deep Java/J2EE architecture expertise with hands-on AI and Generative AI delivery experience. The role will shape AI-first enterprise solutions, embed intelligent capabilities into existing Java estates, and guide clients from experimentation through secure, production-scale adoption.
The successful candidate will operate at the intersection of enterprise architecture, product engineering, cloud-native modernization and applied AI. They will define target architectures, make technology decisions, lead engineering teams, and advise senior stakeholders on how AI can create measurable business and engineering outcomes.
Key responsibilitiesAI and solution architecture
- Define end-to-end architectures for AI-enabled enterprise applications, from data ingestion and retrieval through model orchestration, inference, APIs, user experience and production operations.
- Architect Retrieval-Augmented Generation (RAG), semantic search, knowledge graph, multimodal and agentic AI solutions aligned to business workflows.
- Design multi-agent systems / skills, tool-use patterns and orchestration approaches, including Model Context Protocol (MCP) where relevant.
- Establish architecture blueprints, reusable patterns, non-functional requirements and technology guardrails for scalable, secure and responsible AI adoption.
- Evaluate models, frameworks, data stores and cloud AI services based on quality, latency, security, portability, operability and cost.
Java/J2EE engineering and modernization
- Architect enterprise solutions using Java/J2EE, Spring Boot, Spring MVC, Spring Security and RESTful APIs.
- Integrate LLM-powered services, copilots and AI agents into existing Java applications and business workflows through well-governed APIs and event-driven patterns.
- Decompose monolithic applications into modular services and define modernization pathways that introduce AI without compromising business continuity.
- Design microservices, event-driven and distributed architectures using technologies such as Kafka or RabbitMQ, container platforms and API management.