Java Solution Architect - AI solutions

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Experience: 12+ yrs

Location: Bengaluru, Hyderabad

Job Type: Full-time

We are seeking an experienced Java Solution Architect to lead the design, development, and governance of scalable, cloud-native enterprise applications. This role is ideal for a seasoned technology leader with deep expertise in Java, Spring Boot, microservices, and modern architecture patterns, complemented by hands-on experience building AI-native solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-based AI services.

As a Java Solution Architect, you will define technical strategy, create scalable application architectures, and guide engineering teams through the complete software development lifecycle. You will collaborate with cross-functional stakeholders to design resilient, secure, and high-performing systems while driving architectural best practices, mentoring development teams, and enabling enterprise adoption of AI-powered capabilities. This role requires a strong balance of technical leadership, solution design expertise, and hands-on architectural execution across cloud and enterprise environments.

Key Responsibilities

• Design and own scalable, secure, and cloud-native application architectures for enterprise Java-based platforms.
• Define microservices architecture, integration patterns, and technical roadmaps aligned with business objectives.
• Create and maintain High-Level Design (HLD) and Low-Level Design (LLD) documentation for enterprise solutions.
• Lead architecture reviews and ensure adherence to engineering standards, coding practices, and solution governance.
• Mentor development and quality engineering teams by providing architectural guidance and technical leadership.
• Collaborate with business stakeholders and cross-functional teams to align technical solutions with project priorities and delivery milestones.
• Design and implement AI-native architectures incorporating Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Agentic AI frameworks, and intelligent workflows.
• Integrate enterprise applications with cloud-based AI services while ensuring scalability, reliability, and security.
• Drive DevOps adoption by establishing CI/CD pipelines, deployment automation, and infrastructure best practices.
• Conduct code reviews, identify technical risks, and recommend performance, scalability, and reliability improvements across engineering teams.

What Makes You a Great Fit

• 12+ years of software engineering experience with extensive expertise in enterprise application architecture and solution design.
• Strong hands-on experience designing enterprise systems using Java, Spring Boot, Spring Batch, REST APIs, and microservices architecture.
• Proven experience defining scalable cloud-native architectures across on-premises and cloud environments.
• Hands-on expertise in AI-native architecture, including RAG, LLMs, Agentic AI frameworks, prompt engineering, and cloud AI integration.
• Experience working with Azure cloud services, including Azure OpenAI and enterprise AI deployment strategies.
• Strong knowledge of distributed systems, application scalability, security, and performance optimization.
• Experience with DevOps tools, CI/CD pipelines, Git, Maven, deployment automation, and modern software delivery practices.
• Excellent architectural documentation skills, including HLD, LLD, technical governance, and solution reviews.
• Outstanding communication and stakeholder management skills with the ability to influence technical and business teams.
• A collaborative leadership style with a passion for mentoring engineers, driving innovation, and delivering enterprise-scale AI-enabled software solutions.