Role Summary

Design, build, and maintain end-to-end features across the organization's platform — buyer portals, internal tools, and sales/ops dashboards — while also building LLM-powered features and RAG pipelines alongside the AI Engineering team.
Role split: ~60% full stack engineering, ~40% AI engineering.

Key Responsibilities

- [Full Stack ~60%] Develop responsive front-end interfaces (buyer/investor portals, internal dashboards) and robust back-end services
- [Full Stack ~60%] Design and implement REST/GraphQL APIs and relational database schemas
- [Full Stack ~60%] Write automated tests (unit, integration, e2e) and participate in code reviews
- [Full Stack ~60%] Troubleshoot and resolve production issues; own features end to end
- [AI Engineering ~40%] Build and integrate LLM-powered features (chat assistants, RAG search, AI-assisted workflows) directly into platform code
- [AI Engineering ~40%] Implement RAG pipelines (chunking, embeddings, retrieval) and consume/orchestrate LLM APIs with structured outputs and tool calling
- [AI Engineering ~40%] Integrate AI features with Salesforce (CRM), ERP, and platform services
- Collaborate with product/design and with the core AI Engineering team on shared architecture and standards

Tech Stack

- Frontend: React / Next.js, TypeScript, Tailwind CSS
- Backend: Node.js (NestJS/Express) or Python (FastAPI/Django)
- Databases: PostgreSQL, Redis; some NoSQL (MongoDB) where applicable
- APIs: REST, GraphQL, webhooks
- Cloud/infra: Azure, Docker, CI/CD (GitHub Actions/Azure DevOps)
- AI stack: Anthropic Claude / OpenAI APIs, LangChain or LlamaIndex, pgvector/Azure AI Search for RAG
- Integration: Salesforce REST/Bulk APIs, ERP web services
- Testing: Jest/Playwright/Cypress

Cutting-Edge AI Skills

- Hands-on experience building LLM-powered features end to end, not just consuming an API (~40% of role)
- RAG pipeline construction: chunking, embeddings, retrieval, and citation/grounding




- Prompt/context engineering, structured outputs, and function/tool calling
- Building UI patterns for AI features: chat interfaces, streaming text, citations/sources
- Using AI-assisted development tools (Claude Code, Copilot) to accelerate delivery

Business Domain Exposure

- The organization is a large-scale master real estate developer delivering mixed-use residential, commercial, and hospitality communities across multiple master-planned developments, alongside affiliated retail, wellness/fitness, food & beverage, hospitality, education, and property-management operating brands.
- Building or extending buyer/investor-facing portals for property discovery, unit selection, and payment plans
- Internal tools for sales, project management, and operations teams across master-community projects
- Working alongside Salesforce and ERP consultants to keep platform data consistent end to end

Must-Have Requirements

- Strong proficiency in a up-to-date JS/TS framework (React, Next.js, or similar) — full stack (60%)
- Solid back-end skills (Node.js, Python, or Java) and relational/NoSQL databases — full stack (60%)
- Hands-on experience building LLM/RAG-powered features in production code, not just prototypes — AI engineering (40%)
- Experience designing and consuming APIs, including LLM provider APIs
- Familiarity with Git-based workflows and CI/CD
- Solid written communication for async, distributed teams

Nice to Have

- Experience integrating Salesforce or ERP systems
- Experience with agent frameworks (LangChain, LlamaIndex, or similar)
- Azure cloud experience

Pay: ₹50,000.00 - ₹90,000.00 per month

Education:

- Bachelor's (Preferred)

Experience:

- Full-stack development: 3 years (Preferred)
- Frontend: React / Next.js, TypeScript, Tailwind CSS: 3 years (Preferred)
- Backend: Node.js (NestJS/Express) or Python (FastAPI/Django): 3 years (Preferred)
- Databases: PostgreSQL, Redis; some NoSQL (MongoDB) : 3 years (Preferred)

Work Location: In person

📌 Full Stack Developer (India)
🏢 Unisonal Accounting Solutions
📍 India