Senior AI Developer - Python, Generative AI, RAG, AI Agents (Immediate Joiners

Haridwarbn; Chennai; Hybrid; INR 900,000 - 1,800,000; Full time

Job summary

Independent Recruitment Consultant (freelancer) in Chennai is seeking a Senior AI Developer to design scalable Python applications using FastAPI and generative AI techniques. The role is hybrid, based in Chennai, with cloud and on-prem deployments emphasizing security and cost efficiency.

The ideal candidate has hands-on experience with LangChain, embeddings, vector databases, and has familiarity with AWS, PyTorch or TensorFlow, Kubernetes, and CI/CD pipelines.

Qualifications

• Experience with Python and AI development in production.
• Hands-on with LLMs, prompt engineering, and RAG.
• Experience with Lang Chain/Lang Graph and vector databases.

Responsibilities

• Develop Python applications with FastAPI and REST APIs.
• Implement Generative AI projects involving LLMs, RAG, and prompt engineering.
• Build AI agents, chatbots, and document processing tools.
• Deploy and monitor AI systems on cloud or on-premise and optimize LLM performance.

Skills

Python

FastAPI

LLMs

RAG

LangChain

Embeddings

Vector DB

AI Agents

Chatbots

SQL/NoSQL

Git

CI/CD

Docker

Education

Any graduation

Tools

AWS

PyTorch

TensorFlow

Kubernetes

Job description

Senior AI Developer - Python, Generative AI, RAG, AI Agents (Immediate Joiners Only)Company: Independent Recruitment Consultant (freelancer)Job Location: Chennai, Tamil Nadu, IndiaEmployment Type: Full-timeSalary: 9L18L a yearAbout the RoleWe are seeking an experienced Senior AI Developer to design and implement scalable, production-level AI solutions using Python and advanced generative technologies. This full-time role is based in Chennai with a hybrid working model, focusing on integrating intelligent AI applications into enterprise environments and ensuring security and business value.Primary Responsibilities Develop robust Python applications utilizing FastAPI and RESTful APIs. Work extensively with Generative AI models, including large language models (LLMs), prompt engineering, and retrieval-augmented generation (RAG) techniques. Utilize Lang Chain or Lang Graph frameworks alongside embeddings and vector databases to enhance AI capabilities. Build AI agents, chatbots, and automated document processing systems to streamline workflows. Manage data using SQL and NoSQL databases; apply version control with Git and deploy using Docker and CI/CD pipelines. Deploy and oversee AI applications in both cloud-based and on-premise settings. Focus on optimizing LLM operations (LLMOps), ensuring application security, boosting performance, and controlling costs.Preferred Qualifications Hands-on experience with AWS cloud services, PyTorch or TensorFlow frameworks, Kubernetes orchestration, model fine-tuning, and AI observability tools. Must be ready for immediate joining.Candidate ProfileWe are looking for a practical and innovative problem solver capable of advancing AI projects from initial prototyping phases to full-scale production. The ideal candidate thrives in collaborative, cross-disciplinary teams and builds dependable, secure, and scalable applications.Additional InformationEducation Requirement: Open to any graduates.Responsibilities Develop Python applications with FastAPI and REST APIs. Implement Generative AI projects involving LLMs, prompt engineering, and RAG.Leverage Lang Chain/Lang Graph and embedding/vector database technologies. Create AI agents, chatbots, and document processing tools. Handle SQL/NoSQL databases, Git, Docker, and CI/CD automation. Deploy and monitor AI systems in cloud or on-premise infrastructure. Apply LLMOps best practices focusing on security, performance, and cost reduction.Requirements Strong Python programming skills with relevant AI development experience. Proficient with Generative AI methodologies including LLMs and RAG.Experience using Lang Chain or similar frameworks and vectorized database solutions. Competent in working with SQL and NoSQL databases and version control tools like Git. Knowledge of containerization, CI/CD pipelines, and cloud/on-premise deployments. Familiarity with AWS, PyTorch or TensorFlow, Kubernetes, AI model tuning, and observability. Ability to join immediately. .```