Java Architect
- Keylent
8 Days Ago
NA
W2, C2C
Reading-PA
7-10 Years
Required Skills: AWS, Azure, Java
Job Description
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.
Key Responsibilities
- 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.
AI / LLM / RAG Responsibilities
- 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.
Required Technical Skills
- 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.
Preferred 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
Leadership & Collaboration
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
