Senior Java Architect (Cloud-Native & GenAI Expertise)

Senior Java Architect (Cloud-Native & GenAI Expertise)

Location: Bangalore

Experience: 15-20 years

• Java Architect with 15 - 18 years of experience in software development including 5-8 years in architecture leadership
• Strong communication, stakeholder management, and architectural consulting skills

Architectural Strategy, Leadership and Customer Connect

• Create reference architectures, best practices, blueprints, and governance models for AI-driven systems.
• Expertise in designing and guiding implementation for SOA, Microservices, DDD, Event-driven, serverless applications, web application architecture, data architecture and various integration patterns.
• Impress upon the architectural strategy to customers as practical solutions addressing their pain points directly

Cloud-Native & Hyperscale Infrastructure

• Proven experience developing cloud-native applications.
• In-depth knowledge in cloud infrastructures like AWS, Azure or Google Cloud Platform (GCP)

Modern API & Gen AI driven Application Development

• Lead adoption of GenAI across the enterprise—LLM integration, RAG patterns, AI-assisted development, and automation workflows.
• Partner with product, engineering, and business teams to shape AI-enabled solution roadmaps
• Expertise in core frameworks including Spring, Spring Boot, Spring Security, Spring Integration and Node.Js.
• Experience with application servers/containers like Tomcat, Netty, Jetty, Nginx is a plus.

Programming Proficiency

• Hands-on programming experience with multiple languages, like Java, NodeJS, Python and Go.

Enterprise Technology Implementation

• Practical implementation knowledge of enterprise technologies: Messaging Systems, Elastic Search, Caching (Redis), IAM open standards like OAuth 2.0, JWT

DevOps & Data Engineering

• Good knowledge of Infrastructure as Software (Container Orchestration, Observability, CI/CD) technologies- Docker, Kubernetes, ServiceMesh, Serverless
• Knowledge of big data use cases and technologies such as Data lake, Data pipeline (AWS, Spark, Airflow)

Monitoring & Observability

• Hands-on experience in implementing modern Observability practices across distributed systems (Microservices, Event-Driven) to gauge application health and performance