- Design and develop Generative AI solutions, utilizing OpenAI models and other LLMs.
- Build RAG pipelines for enterprise use cases, optimizing performance and accuracy.
- Implement intelligent workflows with LangChain, LangGraph, and agent-based architectures.
- Refine prompts through prompt engineering for improved AI system performance.
- Integrate vector stores, embeddings, and search systems for semantic retrieval.
- Develop and deploy REST APIs using FastAPI, ensuring security and scalability.
- Manage data pipelines and storage with Azure Blob Storage, and secure credentials with Azure Key Vault.
- Monitor and evaluate LLM applications using observability tools, conducting model evaluation and benchmarking.
- Implement CI/CD pipelines for automated testing and deployment, collaborating with cross-functional teams.
- Strong proficiency in Python, with experience in FastAPI or similar API development frameworks.
- Solid understanding of SQL and database design, and experience with Redis and Celery for data processing.
- Hands-on experience with OpenAI APIs, RAG implementation, and prompt engineering techniques.
- Familiarity with LangChain, LangGraph, and agent-based systems design for intelligent workflows.
- Knowledge of cloud-native architecture, Azure Blob Storage, and Azure Key Vault for cloud integration.
- Experience with model evaluation frameworks and LLM observability tools like LangSmith or Opik.
- Ability to work with version control systems like Git for collaboration and branching.
- Good problem-solving skills, with the ability to adapt to a fast-paced AI landscape.
- Effective communication skills for technical and non-technical discussions.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
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