Full Stack AI Engineer
About the Role
SU:CH AI (part of Shapoorji Pallonji Group) is building AI-powered enterprise platforms across Tax Technology, Compliance, Financial Services, and Enterprise Intelligence.
We are looking for highly skilled Full Stack Engineers with strong expertise in either backend or frontend development, while being comfortable working across the full stack when required.
Hands-on experience with AI technologies, LLM integrations, AI agents, RAG architectures, vector databases, or AI-enabled applications is mandatory.
You will work closely with Product, AI, Design, and Engineering teams to build scalable, secure, and high-performance enterprise applications used by customers in production environments.
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.
Backend-Heavy Full Stack Engineer
Core Skills
Backend Development
- Node.js
- Express.js
- REST APIs & Microservices
- Apache Kafka
- Event-Driven ArchitectureDatabases
- PostgreSQL
- Redis
- Neo4j
- Vector Databases (PgVector, Pinecone, Weaviate, ChromaDB, or equivalent)Security & Identity
- JWT Authentication
- OAuth 2.0 / OpenID Connect (OIDC)
- Role-Based Access Control (RBAC)
- Azure Active Directory (Azure AD)
- Microsoft Graph APIDevOps & Deployment
- Docker & Docker Compose
- Jenkins CI/CD
- Monitoring & Logging
- Performance OptimizationAI Technologies (Mandatory)
- OpenAI / Azure OpenAI / Anthropic / Gemini
- RAG Architectures
- AI Agents & Workflow Automation
- Vector Search & Embeddings
- AI-powered backend workflows
Frontend-Heavy Full Stack Engineer
Core Skills
Frontend Development
- React.js
- Next.js
- TypeScript
- JavaScript (ES6+)
- Redux / Context API
- MUI / MaterioUI Engineering
- Responsive and Mobile-First Design
- Dashboard & Enterprise Application Development
- State Management
- Real-Time User Interfaces
- Frontend Performance OptimizationBackend Familiarity
- Node.js & Express.js
- API Integrations
- Authentication & Authorization
- Database FundamentalsSecurity & Identity
- Azure Active Directory (Azure AD)
- OAuth 2.0 / OIDC
- Microsoft Graph APIAI Technologies (Mandatory)
- AI-Powered User Experiences
- LLM Integrations
- Conversational Interfaces
- AI Copilots & Agent-Based Experiences
- Prompt-Oriented Application Development
Required Experience
- 5-10 years of hands-on experience in Full Stack Development.
- Strong expertise in either Backend Engineering or Frontend Engineering, with working knowledge of the full stack.
- Experience building, deploying, and maintaining production-grade applications used by internal or external users.
- Demonstrated experience delivering features through the complete software development lifecycle, from design and development to deployment and production support.
- Strong understanding of software architecture, scalability, performance optimization, debugging, and application security.
- Hands-on experience building or integrating AI-powered features such as:
- LLM integrations
- RAG-based applications
- AI agents
- Vector databases
- AI-powered search, workflows, or copilots
- Experience working in Agile product development environments.
- Ability to independently own modules and deliver high-quality code with minimal supervision.
Important Requirement
We are specifically looking for engineers who have worked on live production products, not solely on proofs of concept (PoCs), academic projects, hackathons, or experimental implementations.
Candidates should be able to demonstrate:
- Features they have personally built and deployed.
- Production challenges they have solved.
- Scalability, performance, and security considerations they have handled.
- Real business or customer impact of their work.Experience limited to AI experimentation, prompt usage, or personal AI projects without production implementation will not be considered sufficient.
Nice to Have
- Azure Cloud Services
- Kubernetes
- GraphQL
- LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar frameworks
- Experience building AI-native applications at scale
- Exposure to observability and monitoring platforms
What We Value
- Strong engineering fundamentals.
- Product mindset and ownership.
- Ability to thrive in a fast-paced startup environment.
- Passion for AI and emerging technologies.
- High accountability and execution focus.
- Strong problem-solving ability.
- Continuous learning mindset.