QubeLabs Systems - Full Stack Engineer - Enterprise AI Platform

Full Stack Engineer Enterprise AI Platform Location : New Delhi, India (On-site) Employment Type : Full-time About QubeLabs : QubeLabs is building the next generation of Enterprise AI Systems that transform workforce operations and intelligence for the financial services industry. Our platform combines conversational AI, agentic workflow automation, proprietary language models and enterprise intelligence to transform how financial services operate. Our product "QubeLabs Workmate" is purpose-built for banks, NBFCs, MFIs, wealth management firms, insurance companies and fintechs across India and Europe to improve enterprise efficiency, productivity and customer experiences at scale. We're looking for an exceptional Full Stack Engineer who is passionate about building AI-native enterprise software and enjoys working at the intersection of modern software engineering, AI systems and product innovation. Role Overview : As a Full Stack Engineer, you will build and scale the core Enterprise AI Platform powering QubeLabs Workmate. You will work closely with founders, AI engineers, designers and product teams to develop AI-native enterprise applications, real-time conversational interfaces and workflow automation platforms. This role is ideal for engineers who embrace AI-first software development and leverage modern AI engineering tools such as Cursor, Claude Code, GitHub Copilot and similar coding assistants to accelerate development while maintaining production-quality software. You will contribute to scalable platform architecture, AI orchestration interfaces, enterprise integrations and reusable engineering frameworks powering conversational AI, agentic workflows and enterprise intelligence. Key Responsibilities : Platform Engineering : Design and develop scalable AI-native full-stack enterprise applications.Build enterprise dashboards, AI copilots and workflow management platforms.Develop modular APIs, microservices and reusable platform components.Design configurable workflow orchestration, enterprise integrations and event-driven application architectures.Build secure, scalable and high-performance enterprise applications. AI Platform Development : Integrate Large Language Models (LLMs), AI services, orchestration frameworks and enterprise AI capabilities.Develop streaming interfaces for real-time conversational AI and enterprise copilots.Collaborate with AI engineers to integrate model inference, reasoning engines, AI runtimes and workflow orchestration.Build reusable SDKs, APIs and frontend components for AI-powered enterprise applications. Engineering Excellence : Write clean, maintainable and production-ready code.Participate in platform architecture, API design and system engineering discussions.Leverage AI-assisted development tools to significantly improve engineering productivity while maintaining high-quality, secure and scalable software.Follow engineering best practices for testing, security, observability, scalability and performance. Qualifications : Education : Bachelor's or Master's degree in Computer Science, Engineering or a related discipline.Graduates from Tier-1 institutions are preferred. Experience : 3-6 years of experience in Full Stack Software Development.Experience building enterprise SaaS products is preferred.Experience developing modular, API-first, event-driven or distributed applications is highly desirable.Experience with AI-enabled applications, real-time systems, conversational platforms, workflow orchestration or enterprise AI platforms will be an added advantage.Candidates should demonstrate strong proficiency in AI-assisted software engineering and the ability to significantly improve development productivity using modern AI coding tools while maintaining production-grade engineering standards. Required Skills : Frontend : React.js, Next.js, TypeScript, JavaScript (ES6 ), HTML5, CSS3, Tailwind CSS, Responsive UI Development and State Management.Backend : Python, Node.js, NestJS, Express.js, REST APIs, GraphQL, Microservices, Authentication & Authorization, RBAC, API Design, Event-Driven Architecture and WebSockets.Database : PostgreSQL, MongoDB, Redis, Vector Databases (Qdrant, Pinecone or equivalent), Database Design and Performance Optimization.Cloud & DevOps : Docker, Kubernetes, AWS, Azure, GCP, Git, Linux, CI/CD, Containerization, Infrastructure Automation and Monitoring. AI Development : Working knowledge of Large Language Models .