Agentic AI Developer - Data Science

UsefulBI Corporation; Bengaluru; Vor Ort; INR 1.200.000 - 1.800.000; Vollzeit

Zusammenfassung

UsefulBI Corporation is seeking a Generative AI/Agentic AI Developer to design, build, and deploy AI-powered applications leveraging LLMs and multi-agent architectures.

You will work with data engineering and product teams to implement GenAI solutions, optimize prompts, integrate across cloud platforms, and ensure scalable, cost-efficient AI workflows for enterprise use cases.

Qualifikationen

• Strong proficiency in Python and hands-on experience with LLMs.
• Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar.
• Familiarity with vector databases (Pinecone, ChromaDB, FAISS, Weaviate).
• Understanding of NLP, embeddings, semantic search, and AI orchestration.

Aufgaben

• Design and develop GenAI and Agentic AI applications using LLMs.
• Build AI agents, multi-agent workflows, and autonomous task execution systems.
• Develop RAG-based pipelines using vector databases and retrieval frameworks.
• Integrate LLMs into enterprise applications.
• Work with data engineering and product teams for AI solution deployment.

Kenntnisse

Python

LLMs

NLP

Prompt Engineering

Tools

LangChain

LangGraph

CrewAI

LlamaIndex

Pinecone

ChromaDB

FAISS

Weaviate

Docker

FastAPI

Jobbeschreibung

We are looking for a generative AI/Agentic AI Developer with strong experience in large language models (LLMs), AI agents, RAG architectures, and intelligent automation systems. The role involves designing, developing, and deploying next-generation AI-powered applications using modern GenAI frameworks and multi-agent architectures. The ideal candidate should have hands-on experience with LLM ecosystems, prompt engineering, AI orchestration frameworks, vector databases, and cloud-based AI deployments. The candidate will work closely with data engineering, product, and AI teams to build scalable AI-driven solutions for enterprise use cases.

Responsibilities:

• Design and develop GenAI and Agentic AI applications using LLMs.
• Build AI agents, multi-agent workflows, and autonomous task execution systems.
• Develop RAG-based pipelines using vector databases and retrieval frameworks.
• Integrate LLMs such as OpenAI, Claude, Gemini, Llama, or Mistral into enterprise applications.
• Work on prompt engineering, fine-tuning, evaluation, and response optimization.
• Build AI-powered assistants, Q\& A systems, summarizers, automation bots, and intelligent workflows.
• Develop scalable APIs and backend services for AI applications.
• Collaborate with data engineering and product teams for AI solution deployment.
• Optimize model performance, latency, and cost efficiency.

Requirements:

• Strong proficiency in Python.
• Hands-on experience with LLMs and generative AI frameworks.
• Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworks.
• Strong understanding of RAG architecture and vector databases (Pinecone, ChromaDB, FAISS, Weaviate, etc. ).
• Experience with prompt engineering and LLM optimization.
• Exposure to multi-agent systems and agentic AI workflows.
• Knowledge of NLP, embeddings, semantic search, and AI orchestration.
• Experience with REST APIs, FastAPI, or backend integration
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Understanding of CI/CD, Docker, and deployment workflows