
Cutting-Edge AI Applications Developer
20 hours ago
Our team is seeking a seasoned AI professional to spearhead the development of cutting-edge AI-driven applications.
This role involves designing and implementing sophisticated AI agents within our platform, with an initial focus on integrating external large language models (LLMs) via effective prompt engineering and Retrieval-Augmented Generation (RAG) techniques into these agents.
Key Responsibilities- Develop and maintain the core logic for AI agents within scalable FastAPI services. Orchestrate agent tasks, manage state, interact with platform data/workflows, and integrate LLM capabilities.
- Integrate with external LLM provider APIs. Design, implement, and rigorously test effective prompts for diverse retail-specific tasks (generation, Q&A, summarization).
- Implement and optimize RAG patterns using vector databases to provide relevant context to LLM API calls made by agents.
- Build and maintain the containerized FastAPI microservices that host AI Agent logic and handle interactions with LLMs and other platform components in a Docker 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. Stay updated on LLM advancements and be prepared to learn and contribute to potential future in-house LLM fine-tuning and deployment efforts.
- 4-6 years of hands-on experience in software development with a strong focus on AI/ML application development.
- Demonstrable experience integrating and utilizing external LLM APIs (e.g., OpenAI, Anthropic, Google) in applications.
- 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.
- Understanding and practical experience with RAG concepts and vector databases (Pinecone, FAISS, etc.).
- Solid understanding of core Machine Learning concepts and familiarity with frameworks like PyTorch, TensorFlow, or Hugging Face.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker) for application deployment.
- Solid problem-solving skills and clear communication abilities.
- Experience working effectively in an agile environment.
- Willingness and capacity to learn and adapt towards future work involving deeper LLM customization and deployment.
- Bachelor's or Master's degree in Computer Science, AI, or a related field.
- Ability to work independently and collaborate effectively in a remote setting.
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