AI Developer with Python

We are seeking an experienced AI Developer with strong expertise in Python programming, Generative AI, Large Language Models (LLMs), and backend development. The ideal candidate will be responsible for designing, developing, and deploying AI-powered applications using modern GenAI frameworks, RAG architectures, and AI agent technologies. Candidates should have hands-on experience building scalable, production-ready AI solutions and integrating LLMs with enterprise systems., * Design, develop, and maintain AI-powered applications, data pipelines, and microservices using Python.

• Build and implement Generative AI solutions using Large Language Models (LLMs).
• Develop Retrieval-Augmented Generation (RAG) pipelines and AI agent workflows.
• Implement AI agents using frameworks such as LangChain, LangGraph, and CrewAI.
• Integrate LLMs with vector databases, enterprise data sources, and external REST APIs.
• Perform prompt engineering and optimize LLM responses for accuracy and performance.
• Develop backend services and APIs using FastAPI, Flask, or Django.
• Deploy and manage AI applications using Docker and cloud platforms such as AWS, Azure, or GCP.
• Optimize application performance, scalability, reliability, and resource utilization.
• Collaborate with cross-functional teams to deliver enterprise-grade AI solutions.
• Follow software engineering best practices, including testing, version control, and documentation.
• Experience developing autonomous AI agents and multi-agent systems.
• Knowledge of machine learning and deep learning concepts.
• Experience with model deployment, monitoring, and optimization.
• Familiarity with Kubernetes and cloud-native application deployment.
• Experience building enterprise-level AI solutions and scalable architectures.
• Strong analytical, problem-solving, and communication skills.

• 6+ years of overall software development experience with strong Python programming skills.
• Hands-on experience with Generative AI, LLMs, NLP, and Prompt Engineering.
• Strong experience implementing RAG architectures and AI-powered applications.
• Experience with LangChain, LangGraph, CrewAI, or similar AI frameworks.
• Knowledge of vector databases such as Pinecone, ChromaDB, FAISS, or Weaviate.
• Experience working with OpenAI APIs, Azure OpenAI, or other LLM providers.
• Strong knowledge of backend frameworks such as FastAPI, Flask, or Django.
• Experience developing and integrating RESTful APIs and microservices.
• Familiarity with Docker, Git, CI/CD, and MLOps practices.
• Knowledge of cloud platforms such as AWS, Azure, or GCP., * Experience developing autonomous AI agents and multi-agent systems.
• Knowledge of machine learning and deep learning concepts.
• Experience with model deployment, monitoring, and optimization.
• Familiarity with Kubernetes and cloud-native application deployment.
• Experience building enterprise-level AI solutions and scalable architectures.
• Strong analytical, problem-solving, and communication skills.