AI Full StackEngineer
Own the full lifecycle of GenAI-powered products —from model&RAG; integration to production-grade full stack delivery.
- Experience – Mid-level · 3–5 years
- Function – Engineering — AI / Full Stack
- Employment – Full-time · In office / Hybrid
We’re building GenAI-powered applications that combine large language models, retrieval systems, and cloud-native infrastructure. We’re looking for an engineer who can own the full lifecycle — from model and RAG integration through to production-grade full-stack development — and ship independently with minimal oversight.
What You’ll Do
- Design and build end-to-end architecture for AI powered applications, from UI through backend to cloud infrastructure.
- Develop RAG pipelines, integrate LLMs, and build MCP based agentic workflows.
- Build responsive, production-quality front-end interfaces using React.
- Develop and maintain backend services and APIs using Node.js and Python.
- Deploy, scale, and monitor AI workloads on AWS. — Evaluate and monitor LLM/RAG output quality in production.
- Partner closely with product, design, and QA to translate requirements into shipped features.
- Troubleshoot independently and propose solutions — not just surface problems.
Must-Have Skills
CORE EXPERI EN CE
- 3–5 years in software / full-stack development.
- Proficiency in Python.
FU LL STACK DEVELOPM ENT
- Proficiency in React, JavaScript/TypeScript, HTML, and CSS.
- Backend development with Node.js and RESTful API design.
- SQL/NoSQL databases, Git, and version control(GitHub or Bitbucket).
AI & NLP
StrongNLP foundation: tokenization, preprocessing, POS tagging, NER, vectorization (BoW, TF-IDF, Word2Vec/embeddings).
- Solid grasp of transformer architecture (self-attention, multi head attention, positional encoding) and how LLMs are trained.
- Hands-on experience building RAG systems, including hybrid search.
- Prompt engineering — designing, testing, and iterating on prompts for production.
- Vector databases
📌 AI Full Stack Engineer (Pune)
🏢 enreap
📍 Pune