Senior AI Developer (GenAI / LLM)

Role Overview

We are seeking experienced Senior AI Developers with strong expertise in Generative AI and Large Language Models (LLMs). The ideal candidate will have hands-on experience in building, deploying, and optimizing AI-powered applications, with a strong foundation in Python and modern AI/ML frameworks.

Key Responsibilities

AI/ML & GenAI Development

• Design, develop, and deploy AI/ML and GenAI-based applications
• Build and optimize LLM-powered solutions using models such as Gemini, OpenAI, Claude, Mistral, and Llama
• Implement and enhance Retrieval-Augmented Generation (RAG) pipelines, including advanced techniques
• Develop and fine-tune prompt engineering strategies and reusable prompt templates
• Work with agentic frameworks for AI-driven use cases
• Apply guardrails and evaluation frameworks to ensure performance, safety, and reliability

Programming & Data Engineering

• Develop scalable solutions using Python (mandatory)
• Utilize libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, and LlamaIndex
• Integrate GenAI capabilities with enterprise systems via APIs and orchestration tools
• Work with vector databases (PG Vector, Pinecone, MongoDB Atlas, Neo4j)
• Handle and process large volumes of unstructured data

Deployment & MLOps

• Deploy LLM/GenAI models into production environments
• Implement MLOps best practices, including model evaluation and monitoring
• Build and manage CI/CD pipelines using tools like Jenkins, GitLab CI, Azure DevOps, or ArgoCD

Cloud & Infrastructure

• Deploy and manage applications using Kubernetes/OpenShift
• Work in cloud-native environments with scalable and containerized architectures

Required Qualifications

• 8–10 years of experience in application development or systems analysis
• Strong foundation in Machine Learning, NLP, Neural Networks, and Data Science
• Hands-on experience with LLMs and GenAI frameworks
• Proven expertise in RAG pipeline implementation (critical requirement)
• Strong proficiency in Python (mandatory)
• Experience with LLM deployment and MLOps (critical)