We are looking for an experiencedย Java Solution Architectย to lead the design and governance of scalable, secure, and cloud-native enterprise applications. The ideal candidate will bring deep expertise inย Java, Spring Boot, microservices, and enterprise architecture, combined with strong hands-on experience in modernย AI-native architecture patternssuch as RAG, LLMs, agentic frameworks, and Generative AI integrations.
Key Responsibilities
Design and own scalable, secure, and resilientย Java-based application architectures and microservices.
Define technical architecture for enterprise applications across on-premises and cloud environments.
Create and maintainย High-Level Design (HLD) and Low-Level Design (LLD)ย documentation.
Lead architecture reviews and ensure adherence to engineering, coding, security, and architectural standards.
Provide technical leadership and mentor development and QE teams on architecture and implementation decisions.
Collaborate with onshore client and partner teams to align requirements, priorities, technical solutions, and delivery milestones.
Design and implementย AI-native architecturesย using RAG, embeddings, LLMs, and agentic frameworks.
Integrateย Azure OpenAI and other cloud AI servicesย into enterprise applications.
Develop strategies for memory management, context management, and scalability within AI-powered applications.
Evaluate and guide the integration, deployment, and optimisation of Generative AI solutions.
Conduct technical and code reviews across multiple engineering squads.
Drive DevOps automation, CI/CD practices, and reliable deployment processes.
Identify technical risks, architectural gaps, and opportunities for performance, scalability, and maintainability improvements.
Collaborate across business, engineering, security, and technology teams to ensure end-to-end solution alignment.
What Makes You a Great Fit
9+ years of software engineering experience, with 13+ years preferred.
3โ5+ years of experience in solution/application architecture, covering both on-premises and cloud environments.
Expert-level proficiency inย Java, Spring Boot, REST APIs, and Spring Batch.
Strong experience designingย microservices and scalable enterprise applications.
Hands-on experience withย AI-native architecture, including RAG, embeddings, LLMs, agentic frameworks, and Generative AI integrations.
Strong experience withย Azure OpenAI, cloud AI services, LLM deployment, and GenAI application development.
Experience with model fine-tuning and integrating AI capabilities into enterprise applications.
Strong understanding ofย HLD, LLD, system design, architecture patterns, and technical governance.
Experience with DevOps and engineering tools includingย Maven, Git, CI/CD, and Autosys.
Strong understanding of application security, systems development, and enterprise technology architecture.
Excellent problem-solving and analytical skills with the ability to make sound architectural decisions and communicate technical trade-offs.
Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.
Proven ability to lead architecture discussions, conduct code reviews, and mentor engineering teams.
Experience working with distributed, cross-functional, and client-facing teams.
Knowledge ofย Linux and RPM packagingย is an advantage.
Candidates with provenย AI-native architecture experience across RAG, LLMs, and agentic frameworksย will be strongly preferred.
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