
GEN AI Developer
1 day ago
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.
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