Hi All,
Good Morning,
We have an urgent position for the below mentioned requirememt.
Location: Reading, PA
Work Arrangement: 100% Onsite
Experience: 12+ Years
Role: Java Architect
We are seeking an experienced Java Architect to design and lead enterprise application architecture for a major client in Reading, PA.
The ideal candidate will have strong hands-on experience with Java, Spring Boot, React, Kafka, Snowflake, AWS/Azure/Google Cloud Platform, and modern AI/LLM technologies, including RAG (Retrieval-Augmented Generation).
The candidate will be responsible for defining scalable, secure, high-performance application architectures while working closely with engineering, cloud, data, DevOps, and AI teams.
Lead the architecture and design of enterprise-scale applications using Java and Spring Boot.
Define scalable, resilient, secure, and high-performance microservices architectures.
Provide technical leadership across application development, cloud, data, DevOps, and AI initiatives.
Design and develop modern web applications using React and Java-based backend services.
Design and implement event-driven architectures using Apache Kafka.
Define integration patterns between applications, APIs, databases, messaging platforms, and cloud services.
Architect data solutions and application integrations using Snowflake.
Design and support cloud-native applications across AWS, Azure, and Google Cloud Platform.
Evaluate cloud services and recommend the appropriate platform based on application and business requirements.
Design and implement CI/CD pipelines and modern DevOps practices.
Collaborate with DevOps teams to automate application build, testing, deployment, and release processes.
Define application security, scalability, availability, performance, and observability standards.
Lead architecture reviews, technical design sessions, and proof-of-concept initiatives.
Identify opportunities to modernize legacy applications using cloud-native and microservices architectures.
Work closely with engineering teams to establish coding, architecture, integration, and deployment standards.
Troubleshoot complex architectural and production issues and provide long-term technical solutions.
Mentor senior developers and engineers on architecture, design patterns, and modern engineering practices.
Design and support enterprise applications incorporating Generative AI and LLM capabilities.
Evaluate and implement LLM integration patterns within enterprise applications.
Design RAG architectures for connecting LLMs with enterprise data and knowledge sources.
Work with engineering and data teams to develop secure and scalable AI-enabled applications.
Understand vector databases, embeddings, retrieval pipelines, prompt engineering, and LLM integration patterns.
Evaluate emerging AI technologies and identify opportunities to improve business applications using AI.
Ensure AI solutions follow enterprise security, governance, scalability, and data-protection requirements.
12+ years of experience in software engineering and application architecture.
Strong hands-on experience with Java.
Strong experience with Spring Boot and Spring-based microservices.
Strong experience designing microservices and enterprise application architectures.
Hands-on experience with React.
Strong experience with Apache Kafka and event-driven architecture.
Experience with Snowflake and modern cloud data platforms.
Strong experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
Multi-cloud experience across AWS/Azure/Google Cloud Platform is highly preferred.
Strong understanding of CI/CD, DevOps, automation, and cloud-native application development.
Experience with Generative AI, LLMs, and AI application architecture.
Practical experience with RAG architectures.
Strong understanding of REST APIs, API integration, security, scalability, and performance.
Strong architecture documentation, communication, and stakeholder-management skills.
Docker / Kubernetes
OpenShift
Terraform / Infrastructure as Code
Git / GitHub / GitLab
Jenkins / GitHub Actions
AWS Bedrock / Azure OpenAI / Google Vertex AI
Vector databases
LangChain / LangGraph
Python for AI/ML integrations
API Management
OAuth 2.0 / OIDC
PostgreSQL
Redis
Observability and monitoring
Agile/Scrum
The Java Architect will work closely with:
Enterprise and Solution Architects
Application Development Teams
Cloud and DevOps Teams
Data Engineering Teams
AI/ML Teams
Security and Infrastructure Teams
Product and Business Stakeholders
