About the role

Full Stack Engineer (AI-Enabled)

Job Summary:

Join SU:CH AI, a pioneering entity within the Shapoorji Pallonji Group, as we create AI-powered enterprise platforms in Tax Technology, Compliance, Financial Services, and Enterprise Intelligence. We are seeking adept Full Stack Engineers, either backend-heavy or frontend-heavy, to collaborate with cross-functional teams and develop scalable, secure applications that have a real impact on our enterprise clients.

Key Responsibilities:

Design, build, and maintain scalable enterprise-grade web applications.
Develop robust APIs, backend services, and modern user interfaces.
Integrate AI/LLM capabilities into enterprise products and workflows.
Design secure, reliable, and high-performance systems with a strong focus on scalability.
Build and optimize databases, application performance, and system reliability.
Implement authentication, authorization, and enterprise security controls.
Collaborate closely with Product, AI, QA, and Design teams throughout the product lifecycle.
Participate in architecture discussions, code reviews, testing, deployment, and production support.
Contribute to engineering best practices, CI/CD automation, observability, and performance optimization.

Requirements:

4–6 years of hands-on experience in Full Stack Development.
Strong expertise in either Backend Engineering or Frontend Engineering, with a working knowledge of the full stack.
Experience in building, deploying, and maintaining production-grade applications.
Demonstrated experience delivering features through the complete software development lifecycle.
Strong understanding of software architecture, scalability, performance optimization, debugging, and application security.
Hands-on experience with AI technologies, such as LLM integrations, RAG architectures, and vector databases.
Experience working in Agile product development environments.
Capability to independently own modules and deliver high-quality code with minimal supervision.

Preferred Qualifications:

Experience with Azure Cloud Services and Kubernetes.
Familiarity with GraphQL and modern API integrations.
Experience building AI-native applications at scale.
Exposure to observability and monitoring platforms.
Knowledge of frameworks like LangChain, LlamaIndex, or similar tools.