
AI Innovation Specialist
1 day ago
Unlock the Power of Artificial Intelligence with Our Team.
Job Description:We are seeking a skilled Artificial Intelligence Developer to join our team. The ideal candidate will have hands-on experience in designing and developing AI-driven applications, with a focus on Large Language Models (LLMs) and building AI Agents within FastAPI services.
The successful candidate will be responsible for architecting the logic for these agents, enabling them to perform complex tasks within our e-commerce and retail data orchestration pipelines. This includes integrating external LLM APIs via sophisticated prompt engineering and RAG techniques into these agents, built using Python + FastAPI.
As a member of our team, you will work closely with cross-functional teams to deliver AI features, while staying updated on LLM advancements and being prepared to learn and contribute to potential future in-house LLM fine-tuning and deployment efforts.
Key Responsibilities:
- Design, develop, test, and maintain the core logic for AI Agents within FastAPI services.
- Integrate with external LLM provider APIs and design 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.
- Prepare and preprocess data required for effective prompt context, RAG retrieval, and potentially for future fine-tuning tasks.
To succeed in this role, you will need:
- 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.
- 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.
- 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.
While not required, the following qualifications would be beneficial:
- Experience with frameworks like LangChain or LlamaIndex.
- Experience with observability and debugging tools for LLM applications.
- Experience with graph databases and query languages.
- Experience with MLOps practices applicable to both current application monitoring and future model lifecycle management.
- Experience optimizing API call performance or model inference.
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