Gen AI Architect

"AI Solution Architect (13+ Years Experience) Role\: AI Solution Architect / Lead ArchitectExperience\: 11+ YearsRole Summary
We are seeking an experienced AI Solution Architect with a strong Java development background and hands-on expertise in Generative AI, Large Language Models (LLMs), and modern cloud-native architectures. The candidate will be responsible for designing scalable AI solutions, defining architecture standards, and leading enterprise AI initiatives.
Key Responsibilities
Design and implement enterprise-scale AI/GenAI solutions.
Define end-to-end architecture for LLM-powered applications.
Lead technical design discussions and architecture reviews.
Develop AI platforms leveraging Java, Spring Boot, and cloud-native technologies.
Evaluate and integrate LLMs, AI agents, RAG frameworks, and vector databases.
Collaborate with business stakeholders to identify AI use cases and solution roadmaps.
Define security, governance, scalability, and performance standards for AI solutions.
Mentor engineering teams and provide technical leadership.
Implement Harness Engineering using Custom/Predefined Agents and Skills using Microsoft Copilot or Claude Code.
Required Skills
11+ years of software engineering experience.
Strong expertise in Java, Spring Boot, Microservices Architecture.
Hands-on experience with Generative AI and LLM technologies.
Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar platforms.
Strong understanding of RAG, Prompt Engineering, AI Agents, and Vector Databases.
Experience with cloud platforms (AWS/Azure/GCP).
Expertise in API design, event-driven architecture, and distributed systems.
Experience with CI/CD, DevOps, Docker, Kubernetes, and Infrastructure as Code.
Experience in using Claude Code or Github Copilot
Preferred Skills
Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen.
Data Analytics and Machine Learning solution experience.
Architecture certifications in AWS/Azure/GCP.
Experience working in regulated enterprise environments.                        

Design and implement scalable enterprise AI and Generative AI solutions, including end-to-end architecture for LLM-powered applications using Java, Spring Boot, microservices, and cloud-native technologies