Enterprise Architect

Position Title: Java Full-Stack Architect Department: Technology / Engineering Location: Bangalore, Hyderabad, Pune, Gurugram Employment Type: Full-Time Role Summary We are looking for a Java Full-Stack Architect with strong hands-on expertise in Java and a solid grasp of full-stack development, cloud platforms, and AI/ML integration. The ideal candidate has a proven track record of transforming legacy systems into modern architectures and building scalable solutions from the ground up using microservices and contemporary tech stacks. This role demands end-to-end ownership - from design and development to deployment - along with the ability to guide teams, mentor emerging architects, and continuously adapt to evolving technologies. Key Responsibilities Architectural Leadership Own end-to-end architecture across backend, frontend, data, integrations, and AI/ML components. Lead the transformation of existing legacy systems to modern, scalable architectures or architect new systems from scratch using microservices and cloud-native patterns. Define standards for microservices, APIs, UI architecture, and AI/ML integration patterns. Conduct architecture reviews and establish guidelines that ensure quality, scalability, and maintainability. Mentor engineers, groom future architects, and drive a culture of technical excellence within teams. Backend Engineering (Java) Architect and build microservices using latest versions of Java / Spring Boot / Spring Cloud and cloud-native services . Design event-driven systems, asynchronous patterns, and high-performance data pipelines. Integrate AI inference services (REST, gRPC, model-serving APIs) into enterprise applications. Collaborate with data science teams on MLOps practices to productionize ML models. Work with cloud AI services across providers - e.g., AWS Bedrock / SageMaker, Azure OpenAI / Azure ML, GCP Vertex AI. Architect vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. Ensure ethical AI use, security guardrails, and compliance across AI-integrated systems. Frontend Engineering Design modular, scalable UIs using modern frameworks - Angular, React, or Vue - with strong state management. Integrate AI-powered UI capabilities such as copilots, predictive fields, and intelligent search. Ensure seamless front-end consumption of microservices and AI APIs. Willingness to work with any frontend framework depending on project needs; expertise in one is required, openness to others is essential. Cloud & DevOps Architect cloud-native deployments across AWS, Azure, or GCP. Design CI/CD pipelines supporting both microservices and ML model delivery. Implement containerization using Docker / Kubernetes, including GPU workloads where required. Candidates with deep expertise in one cloud provider are expected to be willing to work across other providers (AWS, Azure, GCP) as project needs dictate. Collaboration & Mentoring Guide development teams from design through deployment with hands-on involvement. Work closely with product, data science, UX, and security teams to translate business needs into AI-enabled technical solutions. Actively groom and develop the next generation of architects within the organization. Required Skills & Experience Core Technical Skills Backend (Java): Latest versions of Java, Spring Boot, Spring Cloud, REST, JPA / Hibernate Frontend: Proficiency in at least one of: Angular, React, Vue; TypeScript, HTML, CSS Openness to learn and work across frameworks as needed Architecture: Microservices, distributed architecture, DDD, event-driven design Strong experience in legacy-to-modern system transformation or greenfield architecture Cloud: Hands-on expertise in at least one of: AWS, Azure, GCP Willingness and adaptability to work across cloud providers as required Database: Relational + NoSQL (MongoDB, Cassandra); vector DBs (Pinecone, Redis Vector, Milvus - preferred) AI/ML Skills Hands-on experience integrating AI APIs (OpenAI, Azure OpenAI, Vertex AI, Bedrock). Working knowledge of the ML lifecycle: training, evaluation, deployment, and monitoring. Experience with RAG architecture, embeddings, or LLM orchestration frameworks (LangChain, Semantic Kernel, Haystack). Ability to design MLOps workflows (CI/CD for models, versioning, drift detection). Willingness to learn and adopt new AI/ML tools and frameworks as the landscape evolves. Familiarity with Python-based ML frameworks (nice to have): PyTorch, TensorFlow, Scikit-learn. Soft Skills Strong communication, leadership, and stakeholder management skills. Ability to translate complex technical concepts - including AI - into business value. Deep problem-solving mindset with a focus on practical, production-grade solutions. Growth mindset: willingness to learn and work with new stacks, tools, and platforms as demanded by the project. Preferred Qualifications Bachelor's or Master's in Computer Science or a related field. Certifications: Cloud Architect (AWS / Azure / GCP), Generative AI / ML certifications (preferred), Java Architecture certifications. Experience with data engineering, ETL, or streaming platforms (Kafka). Exposure to privacy, responsible AI, and security frameworks. Key Performance Indicators (KPIs) Quality and scalability of architectures delivered (new builds and legacy transformations). Successful end-to-end delivery - from design to production deployment. Adoption and effective integration of AI/ML features across products. Reduction in latency, cost, and technical debt. Developer enablement through frameworks, standards, and best practices. Measurable growth and readiness of mentored engineers and future architects.