GEN AI Developer

We are seeking a skilled Senior Python Engineer with a strong foundation in backend engineering and hands-on experience in Generative AI. The ideal candidate will have at least 3+ years of core Python development and 1-1.5 years of experience building and deploying AI-powered applications. This role is best suited for individuals who enjoy developing scalable AI-driven services, writing production-grade code, and collaborating with cross-functional teams to deliver enterprise-ready AI solutions.

Responsibilities

• Develop and maintain Python-based microservices integrating Generative AI capabilities.
• Build and optimize GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration tools.
• Implement RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI, Azure OpenAI, or open-source LLMs.
• Collaborate with DevOps engineers to support CI/CD, containerization, and monitoring for GenAI pipelines.
• Work with ML engineers and data scientists to optimize AI models for performance and scalability.
• Participate in design discussions, contribute to code reviews, and ensure adherence to engineering best practices.
• Experiment with agentic workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel.
  

Requirements

• Strong proficiency in Python development with experience in frameworks like FastAPI, Flask, and asyncio.
• Good understanding of microservices architecture and distributed systems.
• Hands-on experience with GenAI frameworks: LangChain, LlamaIndex, Hugging Face Transformers.
• Exposure to cloud platforms, preferably Azure (Azure OpenAI), for deploying LLM-based services.
• Experience with REST API design and external service integration.
• Familiarity with vector databases such as FAISS, Pinecone, or Weaviate.
• Working knowledge of DevOps concepts (Docker, GitHub Actions, Kubernetes).
• Exposure to agentic orchestration frameworks like Autogen, LangGraph, or Semantic Kernel.
• Experience with fine-tuning or customizing open-source LLMs.
• Understanding of observability, logging, and performance tuning in AI systems.
• Familiarity with MLOps practices and collaboration with ML/Data Science teams.
• Agile development experience with cross-functional engineering collaboration.
  

This job was posted by Careers Techchefz from TechChefz.