Key Responsibilities:
- Develop and integrate Generative AI/LLM applications.
- Build RAG pipelines using embeddings, vector databases, and document processing.
- Work with models such as GPT, Claude, Gemini, Llama, or similar LLMs.
- Develop effective prompt engineering strategies and evaluate model outputs.
- Build AI agents and tool-calling workflows.
- Develop APIs and backend services using Python/FastAPI or similar frameworks.
- Work with vector databases such as Pinecone, FAISS, Weaviate, or Chroma.
- Implement model evaluation, monitoring, security, and optimization.
- Collaborate with data scientists, software engineers, and product teams.
- Deploy AI solutions using cloud platforms such as AWS, Azure, or GCP.
Required Skills:
- Strong Python programming.
- Good understanding of Machine Learning, NLP, and Deep Learning.
- Experience with LLMs, RAG, embeddings, and prompt engineering.
- Knowledge of frameworks such as LangChain, LlamaIndex, or similar.
- Experience with REST APIs and Git.
- Understanding of databases and vector databases.
- Familiarity with Docker and cloud deployment.