Job Description
Own the full lifecycle of GenAI-powered products — from model & RAG integration to production-grade full-stack delivery.
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nExperience · 3–5 years
nFunction: Engineering-AI+Full Stack
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nWe'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.
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nWhat You'll Do:
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n— Design and build end-to-end architecture for AI-powered applications, from UI through backend to cloud infrastructure.
n— Develop RAG pipelines, integrate LLMs, and build MCP-based agentic workflows.
n— Build responsive, production-quality front-end interfaces using React.
n— Develop and maintain backend services and APIs using Node.js and Python.
n— Deploy, scale, and monitor AI workloads on AWS.
n— Evaluate and monitor LLM/RAG output quality in production.
n— Partner closely with product, design,



and QA to translate requirements into shipped features.
n— Troubleshoot independently and propose solutions — not just surface problems.
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nMust-Have Skills:
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n• 3–5 years in software / full-stack development.
n• Proficiency in Python.
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nFull Stack Development:
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n• Proficiency in React, JavaScript/TypeScript, HTML, and CSS.
n• Backend development with Node.js and RESTful API design.
n• SQL/NoSQL databases, Git, and version control (GitHub or Bitbucket).
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nAI & NLP:
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n• Solid NLP foundation: tokenization, preprocessing, POS tagging, NER, vectorization (BoW, TF-IDF, Word2Vec/embeddings).
n• Solid grasp of transformer architecture (self-attention, multi-head attention, positional encoding) and how LLMs are trained.
n• Hands-on experience building RAG systems, including hybrid search.
n• Prompt engineering — designing, testing, and iterating on prompts for production.
n• Vector databas

📌 Senior AI Full Stack Engineer (Pune)
🏢 enreap
📍 Pune