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Niche generative AI stack and vector DB experience reduces applicant density.
Role requires specialized GenAI, LangChain, vector DB and GCP skills, limiting cross-industry transferability.
Extensive mandatory tech stack and specialized GenAI/GCP requirements enforce strict filtering.
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Develop and deploy full-stack Generative AI and Agentic AI applications, covering frontend (React/Angular/Svelte), backend (Python, FastAPI), AI agents, and cloud infrastructure on GCP.
Build and maintain scalable backend services, REST APIs, multi-agent workflows, and RAG solutions using embeddings and vector databases like Vertex AI, pgvector, Pinecone, etc.
Implement secure authentication, CI/CD pipelines, monitoring, logging, and optimize applications for performance, scalability, reliability, and cost in production environments.
Proficient in frontend frameworks: React, Angular, or Svelte; JavaScript/TypeScript and REST API integration.
Strong backend skills with Python, FastAPI, asynchronous programming, and SQL/PostgreSQL.
Experience with Generative AI technologies: Gemini/Vertex AI, LangChain, LangGraph, RAG, embeddings, vector databases.
Work Experience Required: Not explicitly mentioned in the JD. B.Tech/B.E, BCA, or BSc in any specialization mandatory.
Experienced full-stack AI engineer capable of independently delivering end-to-end scalable AI solutions from UI to backend to AI agents and cloud deployment.
Strong software engineering skills combined with hands-on expertise in Generative AI frameworks, cloud technologies (GCP), and production monitoring.
Comfortable managing complex AI workflows including multi-agent systems, prompt engineering, secure authentication, and enterprise-grade application requirements.