JAVA + AI Architect

Job Summary We are seeking a highly experienced Java + AI Architect to lead the design and implementation of enterprise-scale applications powered by Artificial Intelligence and Generative AI. The ideal candidate will have deep expertise in Java-based application architecture, cloud-native technologies, AI/ML platforms, Large Language Models (LLMs), and enterprise integration patterns. Key Responsibilities • Define and drive the architecture for Java-based enterprise applications integrated with AI capabilities. • Design scalable, secure, and high-performance AI-powered solutions using modern architectural principles. • Lead the adoption of Generative AI, Machine Learning, and Agentic AI across enterprise platforms. • Architect and implement AI use cases such as chatbots, intelligent assistants, document processing, knowledge search, and recommendation engines. • Design Retrieval-Augmented Generation (RAG) frameworks and vector-based search architectures. • Integrate LLMs and AI services with enterprise systems using APIs and microservices. • Collaborate with business stakeholders, product teams, engineering teams, and leadership to translate business requirements into technical solutions. • Define best practices, coding standards, security standards, and architecture guidelines. • Provide technical leadership, mentoring, and guidance to development teams. • Drive solution reviews, performance optimization, and scalability assessments. Required Skills Java Architecture • Strong expertise in Java 8/11/17+. • Extensive experience with: • Spring Boot • Spring Cloud • Microservices Architecture • REST APIs • Event-Driven Architecture • Distributed Systems • Experience with: • Kafka • RabbitMQ • ActiveMQ • Strong understanding of: • Design Patterns • Domain-Driven Design (DDD) • SOLID Principles • Enterprise Integration Patterns AI & Generative AI • Deep understanding of: • Machine Learning • Deep Learning • Natural Language Processing (NLP) • Generative AI • Large Language Models (LLMs) • Experience with: • OpenAI • Azure OpenAI • AWS Bedrock • Google Vertex AI • Anthropic Claude • Open-Source Models (Llama, Mistral, etc.) • Hands-on experience in: • Prompt Engineering • Fine-Tuning • RAG Architecture • Vector Databases • AI Agents • AI Governance AI Frameworks & Tools • Experience with: • LangChain • LangGraph • LlamaIndex • Semantic Kernel • CrewAI • AutoGen • Vector Databases: • Pinecone • ChromaDB • Weaviate • FAISS Cloud & DevOps • Expertise in one or more cloud platforms: • Microsoft Azure • AWS • Google Cloud Platform (GCP) • Experience with: • Docker • Kubernetes • OpenShift • CI/CD Pipelines • Terraform Data Technologies • Strong knowledge of: • SQL • NoSQL Databases • Data Warehousing • Data Pipelines • Apache Spark • Databricks Leadership Responsibilities • Lead architecture governance and technology roadmap initiatives. • Conduct architecture and code reviews. • Mentor architects, technical leads, and development teams. • Evaluate new AI technologies and recommend adoption strategies. • Engage with clients and leadership teams on solution strategy and innovation initiatives. Preferred Skills • Experience in building enterprise AI platforms. • Knowledge of MLOps and Model Lifecycle Management. • Experience with AI security, Responsible AI, and compliance frameworks. • Exposure to Retail, BFSI, Healthcare, or Manufacturing domains. • AI and Cloud certifications from Microsoft, AWS, Google, or equivalent. Educational Qualification • Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field. Soft Skills • Excellent stakeholder management and communication skills. • Strong analytical and problem-solving abilities. • Strategic thinking and decision-making capabilities. • Ability to lead globally distributed teams. • Strong consulting and client-facing skills. Nice to Have • Experience designing enterprise-scale AI transformation programs. • Knowledge of Multi-Agent Architectures and Autonomous AI Systems. • Published technical papers, patents, or conference presentations in AI or enterprise architecture. • Experience with AI Centers of Excellence (CoE) and innovation initiatives.