PYTHON DEVELOPER GENAI & AGENTIC AI

<p>We are seeking a highly skilled Python Developer with strong expertise in Generative AI and Agentic AI frameworks to join our team. The ideal candidate will have hands-on experience building intelligent AI solutions, integrating large language models (LLMs), and developing autonomous AI agents capable of reasoning and task execution. Experience with Elasticsearch is desirable.</p><ul><li>Design, develop, and deploy AI-powered applications using Python.</li><li>Build and implement Generative AI solutions leveraging Large Language Models (LLMs).</li><li>Develop and orchestrate Agentic AI workflows, including autonomous agents capable of planning, reasoning, and executing tasks.</li><li>Integrate AI models with enterprise applications and external APIs.</li><li>Create robust prompts, retrieval pipelines, and agent architectures to solve business problems.</li><li>Optimize AI applications for performance, scalability, and reliability.</li><li>Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.</li><li>Implement best practices for testing, monitoring, and deployment of AI applications.</li><li>Utilize Elasticsearch for indexing, searching, and retrieval use cases where applicable.</li><li>Stay current with emerging trends and advancements in GenAI and Agentic AI technologies.</li></ul> <ul><li>Strong programming experience in Python.</li><li>Hands-on experience with Generative AI technologies and LLM-based application development.</li><li>Proven experience designing and implementing Agentic AI solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.</li><li>Experience working with prompt engineering, RAG (Retrieval-Augmented Generation), and AI orchestration patterns.</li><li>Knowledge of integrating AI services and APIs from leading model providers.</li><li>Familiarity with vector databases and embeddings.</li><li>Strong problem-solving skills and understanding of software engineering best practices.</li></ul><p><strong>Good to Have</strong></p><ul><li>Experience with Elasticsearch for search and retrieval implementations.</li><li>Exposure to cloud platforms such as AWS, Azure, or Google Cloud.</li><li>Experience with containerization technologies such as Docker and Kubernetes.</li><li>Understanding of MLOps practices and AI application deployment.</li></ul>