Gen AI/ML Engineer

Photon; Hyderabad, Chennai District, Bengaluru; On-site; INR 2,400,000 - 4,000,000; Full time

Job summary

Photon is seeking a Generative AI Engineer in Hyderabad to design, optimize and scale production-ready AI applications. You will build multi-agent systems, develop sophisticated RAG pipelines, and deploy both frontier and local LLMs.

You will orchestrate AI workflows, integrate multiple LLMs, and design scalable backend services using FastAPI. Expect hands-on work with LangChain, LlamaIndex and vector databases, plus model fine-tuning with PyTorch/TensorFlow in a production setting.

Qualifications

• Hands-on experience building production-grade GenAI apps.
• Strong Python and AI framework knowledge.
• Experience with RAG, embeddings and vector search.

Responsibilities

• Develop and orchestrate AI workflows using LangGraph and multi-agent architectures.
• Build advanced RAG systems with LlamaIndex and vector databases.
• Integrate multiple LLMs (OpenAI, Claude, Llama, etc.) based on use case.
• Design scalable backend services using FastAPI and async Python.
• Fine-tune LLMs using PyTorch/TensorFlow.
• Optimize performance (latency, cost, reliability).
• Deploy AI services using Docker in production environments.

Skills

Python

Async programming

AI frameworks

CI/CD

Security

Tools

LangGraph

LlamaIndex

Vector databases

Docker

FastAPI

Hugging Face

PostgreSQL

Job description

Role Summary:
We are looking for a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will work on designing multi-agent systems, advanced RAG pipelines, and deploying both frontier and local LLMs.

Key Responsibilities

• Develop and orchestrate AI workflows using LangGraph and multi-agent architectures
• Build advanced RAG systems with LlamaIndex and vector databases
• Integrate multiple LLMs (OpenAI, Claude, Llama, etc.) based on use case
• Design scalable backend services using FastAPI and async Python
• Fine-tune LLMs using PyTorch/TensorFlow
• Optimize performance (latency, cost, reliability)
• Deploy AI services using Docker in production environments

Tech Stack

• LLMs: Gemini, OpenAI, Claude, Llama
• Frameworks: LangChain, LlamaIndex, Hugging Face
• Backend: Python, FastAPI, Async Programming
• Data: PostgreSQL, Vector DBs
• ML: PyTorch, TensorFlow
• Tools: Prompt Engineering, GenAI Optimization, Monitoring

What We’re Looking For

• Hands-on experience with production-grade GenAI applications
• Strong Python and AI framework knowledge
• Experience with RAG, embeddings, and vector search
• Understanding of LLM fine-tuning and local deployment
• Exposure to CI/CD, monitoring, and API security