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Evnek - Generative AI Full Stack Engineer

Evnek
4 - 12 Years
Multiple Locations

Posted on: 26/08/2026

Job Description

Job Title : GenAI Engineer Full Stack

Experience : 4 - 12 Years

Location : Bengaluru

Notice Period : Immediate Joiners Only

Employment Type : Full-Time

About the Role :

We are looking for a hands-on Generative AI Engineer with strong Full Stack development experience to design, develop, and deploy production-grade AI applications. The ideal candidate should have expertise in LLMs, RAG, AI Agents, Python, APIs, modern frontend frameworks, databases, and cloud technologies.

The role requires an engineer who can take complete ownership of AI applicationsfrom solution design and backend development to frontend integration, deployment, and production support.

Key Responsibilities :

- Design, develop, and deploy end-to-end Generative AI applications for enterprise use cases.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines.

- Develop LLM workflows, AI Agents, and multi-agent solutions.

- Integrate LLMs such as OpenAI/Azure OpenAI, Claude, Gemini, or open-source models into enterprise applications.

- Implement prompt engineering, function/tool calling, structured outputs, and LLM evaluation techniques.

- Develop scalable backend services and REST APIs using Python, FastAPI, or Flask.

- Build responsive frontend applications using React.js, Next.js, Angular, or similar frameworks.

- Integrate GenAI solutions with enterprise applications, APIs, databases, and third-party platforms.

- Work with Vector Databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search.

- Implement document ingestion, chunking, embedding, retrieval, reranking, and response-generation pipelines.

- Deploy and manage AI applications on Azure, AWS, or GCP.

- Implement authentication, security, logging, monitoring, and performance optimization.

- Work closely with Product, Data, AI, and business teams to translate requirements into production-ready solutions.

- Troubleshoot production issues and continuously improve AI application quality, latency, accuracy, and scalability.

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