At Agile Dream Team, we are committed to innovation and excellence, leveraging cutting-edge AI technologies to empower businesses. We are looking for a highly skilled AI Agent Developer to join our dynamic team and build advanced AI-driven solutions. Learn more about us at: www.agiledreamteam.com

REQUIRED SKILLS & EXPERIENCE

• Proficiency in AI/ML frameworks: TensorFlow, PyTorch, LangChain, OpenAI API, Hugging Face, or similar.
• Strong experience in NLP, LLM fine-tuning, and embedding models.
• Hands-on experience with retrieval-augmented generation (RAG) and prompt engineering.
• Expertise in Python, FastAPI, Flask, or similar backend frameworks.
• Experience with vector databases (Pinecone, Weaviate, FAISS, ChromaDB, etc.).
• Knowledge of cloud services (AWS, Azure, or GCP) and serverless architectures.
• Experience integrating AI with API-driven applications and automation workflows.
• Familiarity with CI/CD pipelines, version control (Git), and Agile methodologies.
• Strong problem-solving and analytical skills, with a passion for AI innovation.

PREFERRED QUALIFICATIONS

• Experience with multi-agent architectures and AI-driven decision-making systems.
• Understanding of graph neural networks (GNNs) and symbolic AI.
• Experience with LLM orchestration tools such as AutoGPT, BabyAGI, CrewAI, or OpenDevin.
• Contributions to open-source AI projects or publications in AI/ML research.
• Knowledge of ethical AI principles and responsible AI deployment.

ROLE OVERVIEW

As an AI Agent Developer, you will be responsible for designing, developing, and optimizing AI-powered agents that leverage machine learning, natural language processing (NLP), and automation frameworks. Your expertise will contribute to creating intelligent solutions that enhance business operations, customer interactions, and automation workflows.

KEY RESPONSIBILITIES

• Design and develop AI-driven agents for customer service, process automation, and knowledge retrieval.
• Implement LLMs (Large Language Models) and NLP techniques to improve AI agent capabilities.
• Optimize prompt engineering and retrieval-augmented generation (RAG) techniques for efficiency and accuracy.
• Integrate AI models with APIs, cloud services, and existing enterprise systems.
• Fine-tune AI models and continuously improve their context awareness and problem-solving capabilities.
• Work with vector databases, embeddings, and knowledge graphs for AI memory and reasoning.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deploy AI-driven solutions.
• Monitor and improve AI performance using A/B testing, feedback loops, and real-world user interactions.