Java Fullstack Technical Architect

Position Title: Java Full-Stack Architect

Department: Technology / Engineering

Location: Bangalore, Hyderabad, Pune, Gurugram

Employment Type: Full-Time

We need resources to work on hybrid model which is 2 to 3 days in a week.

Looking for early joiners for immediate projects.

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.