Solution Architect–JVM

Responsibilities

• Solution Architecture Translate client business needs into executable full-stack architectures and technology roadmaps.
• Design distributed, microservices-based, API-first, and event-driven architectures using Java and modern web technologies.
• Develop scalable, secure, and cloud-ready architecture designs aligned with business requirements.
• Design AI-enabled and agentic applications involving LLMs, Retrieval-Augmented Generation (RAG), AI orchestration, and enterprise knowledge systems.
• Architect enterprise applications using Java, Spring Boot, Spring Cloud, Hibernate, and related JVM technologies.
• Define best practices for microservices, API design, integration patterns, and messaging systems such as Kafka and RabbitMQ.
• Create high-level and low-level architecture designs (HLDs/LLDs).
• Drive AI-native and AI-assisted engineering practices across the software development lifecycle, from requirements and architecture through development, testing, deployment, and operations.
• Client Engagement & Pre-Sales Support
• Lead solutioning for RFPs/RFIs and proposal responses, including developing, presenting, and defending technical solutions.
• Evaluate tools and frameworks and define modernization and migration strategies.
• Present architecture decisions, technical trade-offs, and estimates to client stakeholders, including C-level executives.
• Support effort estimation, risk identification, and technical feasibility assessments.
• Act as a trusted advisor to clients' technology leadership.
• Take ownership of solution development, proposal activities, and client discussions, building strong client relationships.
• Balance pre-sales responsibilities with hands-on, potentially billable client engagements.
• This role is not limited to pre-sales or advisory work.
• Delivery Governance & Engineering Excellence Conduct architecture reviews and ensure alignment with enterprise standards.
• Establish best practices for scalability, security, observability, performance, and high availability.
• Collaborate with DevOps teams on CI/CD, Docker, Kubernetes, and cloud infrastructure.
• Ensure AI-enabled solutions address data security, privacy, governance, observability, model risk, and cost management.
• Work with engineering teams to ensure architecture designs are implemented effectively.
• Leadership & Mentorship Mentor technical leads and senior engineers.
• Guide cross-functional teams across backend, frontend, DevOps, and QA.
• Promote knowledge sharing, engineering excellence, and capability development.
• Demonstrate ownership, initiative, and executive presence while independently driving solutioning activities and client engagements.