GenAI Developer

Elabs Infotech; Hyderabad, Chennai, Bengaluru; Hybrid; INR 1,800,000 - 2,800,000; Full time

Benefits offered by this job

Restaurant d'entreprise

Indemnités de stage/alternance

Job summary

Elabs Infotech is seeking skilled GenAI Developers to design, build, and deploy AI-powered applications using LLMs, RAG, and modern AI frameworks. You will work with Python, LangChain, and cloud platforms to deliver enterprise-grade AI solutions.

Responsibilities include building scalable backend services, integrating LLMs with APIs and databases, and deploying on AWS/Azure/GCP with MLOps practices. Collaboration with cross-functional teams is essential for production readiness.

Qualifications

• Experience building GenAI apps and LLM integrations.
• Hands-on with Python and cloud platforms (AWS/Azure/GCP).
• Familiar with LangChain/LangGraph and RAG pipelines.

Responsibilities

• Develop and deploy Generative AI applications using LLMs.
• Design and implement RAG pipelines for enterprise use cases.
• Build AI agents and agentic workflows using LangChain/LangGraph.
• Integrate LLMs with APIs, databases, vector stores, and enterprise systems.
• Develop scalable backend services and REST APIs using Python.
• Optimize prompts, retrieval strategies, and LLM app performance.
• Deploy AI solutions on AWS, Azure, or GCP.
• Implement CI/CD, Docker, Kubernetes, monitoring, and MLOps.
• Collaborate with engineering, product, and business teams.

Skills

Generative AI

LLMs

RAG

LangChain

LangGraph

Python

ML fundamentals

AWS

Azure

GCP

Tools

Docker

Kubernetes

FastAPI

REST APIs

Job description

Experience: 520 Years, depending on level

Location: PAN India / Project Location

Notice Period: Immediate to 30 Days preferred

Job Description

We are seeking skilled GenAI Developers to design, build, and deploy AI-powered applications using Large Language Models, Retrieval-Augmented Generation (RAG), and modern AI frameworks. Candidates should have hands-on experience in Python, LLM application development, and at least one cloud platformAWS, Azure, or GCP.

Key Responsibilities

• Develop and deploy Generative AI applications using LLMs.
• Design and implement RAG pipelines for enterprise use cases.
• Build AI agents and agentic workflows using frameworks such as LangChain and LangGraph.
• Integrate LLMs with APIs, databases, vector stores, and enterprise systems.
• Develop scalable backend services and REST APIs using Python.
• Optimize prompts, retrieval strategies, and LLM application performance.
• Deploy AI solutions on AWS, Azure, or GCP.
• Implement CI/CD, Docker, Kubernetes, monitoring, and MLOps practices as required.
• Collaborate with engineering, product, and business teams to deliver production-ready AI solutions.

Mandatory Skills

• Generative AI and Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• LangChain and/or LangGraph
• Python programming
• Machine Learning fundamentals
• Hands-on experience with at least one cloud platform: AWS, Azure, or GCP

Good to Have

• Agentic AI and Model Context Protocol (MCP)
• LLM fine-tuning and prompt engineering
• Vector databases such as Pinecone, FAISS, Chroma, or Qdrant
• FastAPI / Flask and REST API development
• Docker, Kubernetes, CI/CD, and MLOps
• Production deployment, monitoring, and LLM evaluation

Level-Based Expectations

• Developer: Hands-on implementation of LLM, RAG, and GenAI applications.
• Lead: Technical ownership, solution delivery, code reviews, and team coordination.
• Architect: End-to-end GenAI architecture, cloud solution design, scalability, security, governance, and technical leadership.

Interested candidates can share their updated resumes along with total experience, relevant GenAI experience, current location, notice period, and current CTC/expected CTC.