AI Engineer

• Design, develop, and implement a RAG-based AI Application for the healthcare sector, prioritizing data security, compliance, and privacy (HIPAA / SOC2-ready).
• Build and integrate RAG pipelines combining semantic search, embeddings, and LLMs for secure contextual responses.
• Develop agentic AI workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, Auto-GPT, and BabyAGI.
• Integrate both open-source LLMs (LLaMA, Mistral, Falcon) and enterprise LLMs (OpenAI, Anthropic, Cohere), optimizing performance and cost.
• Configure and manage vector databases (Pinecone, FAISS, Weaviate) for efficient knowledge retrieval and storage.
• Deploy AI solutions on AWS (Lambda, S3, QuickSight, API Gateway) following security and scalability best practices.
• Design and integrate REST and GraphQL APIs, ensuring system interoperability and reliability.
• Collaborate with product, UX, and data science teams to transform prototypes into SaaS-ready MVPs, delivering seamless chat, voice, and dashboard experiences.

Senior AI Engineer – RAG, LLMs

AI Engineer

AI Engineer – RAG, Agents

AI Engineer