
AI Solution Developer
1 day ago
As a seasoned AI developer, you will be responsible for crafting innovative AI-driven solutions utilizing Large Language Models (LLMs) and developing sophisticated AI agents within our platform. You will design the architecture for these agents, enabling them to perform complex tasks within our e-commerce and retail data orchestration pipelines.
Key Responsibilities:- Design, develop, test, and maintain the core logic for AI agents within FastAPI services.
- Integrate with external LLM provider APIs, design, implement, and rigorously test effective prompts for diverse retail-specific tasks.
- Implement and optimize Retrieval-Augmented Generation (RAG) patterns using vector databases to provide relevant context to LLM API calls made by agents.
- Build and maintain scalable FastAPI microservices that host AI agent logic and handle interactions with LLMs and other platform components in a containerized environment.
- Prepare and preprocess data required for effective prompt context, RAG retrieval, and potentially for future fine-tuning tasks.
- Collaborate with cross-functional teams to deliver AI features and stay updated on LLM advancements.
- Hands-on experience in software development with a strong focus on AI/ML application development.
- Demonstrable experience integrating and utilizing external LLM APIs.
- Proven experience with Prompt Engineering techniques.
- Strong Python programming skills.
- Practical experience building and deploying RESTful APIs using FastAPI.
- Experience designing and implementing application logic for AI-driven features or agents.
- Solid understanding of core Machine Learning concepts and familiarity with frameworks like PyTorch, TensorFlow, or Hugging Face.
- Familiarity with cloud platforms and containerization for application deployment.
- Solid problem-solving skills and clear communication abilities.
- Experience working effectively in an agile environment.
- Experience with frameworks like LangChain or LlamaIndex.
- Experience with observability and debugging tools for LLM applications.
- Experience with graph databases and query languages.
- Experience optimizing API call performance or model inference.
- Knowledge of AI security considerations and bias mitigation.
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