Guru Schools
Position Title
* Applied AI Engineer
Position Responsibilities
Title:
AI Engineer
Location : Houston TX, /Onsite in Houston office 3 days per week.
Duatio:18 to 20 Months Contract
Minimum Requirements:
Bachelor's or Master's degree in Computer Science, AI/ML, or a related field. 5+ years of software development experience with strong Python skills. 2-3+ years of hands-on experience building GenAI/LLM-based applications. Experience developing multi-step agent workflows using LangGraph or similar orchestration frameworks. Proficient in designing retrieval pipelines: document loaders, chunking strategies, embedding models, and vector database integration. Strong grasp of GenAI concepts, including: Retrieval-Augmented Generation (RAG) Embeddings & vector databases (e.g., FAISS, Pinecone, ChromaDB) Prompt engineering and fine-tuning LLM APIs (e.g., OpenAI, Claude, Gemini) Experience deploying cloud-native solutions using GCP and/or Azure. Solid understanding of API design, microservices, and software architecture patterns. Familiarity with version control systems (e.g., Git, Azure DevOps). Experience with Docker and Kubernetes. Demonstrated ability to build and scale AI/ML solutions from proof-of-concept to production.
Skills:
GenAI/LLM,AI/ML
* Applied AI Engineer
Position Responsibilities
Title:
AI Engineer
Location : Houston TX, /Onsite in Houston office 3 days per week.
Duatio:18 to 20 Months Contract
Minimum Requirements:
Bachelor's or Master's degree in Computer Science, AI/ML, or a related field. 5+ years of software development experience with strong Python skills. 2-3+ years of hands-on experience building GenAI/LLM-based applications. Experience developing multi-step agent workflows using LangGraph or similar orchestration frameworks. Proficient in designing retrieval pipelines: document loaders, chunking strategies, embedding models, and vector database integration. Strong grasp of GenAI concepts, including: Retrieval-Augmented Generation (RAG) Embeddings & vector databases (e.g., FAISS, Pinecone, ChromaDB) Prompt engineering and fine-tuning LLM APIs (e.g., OpenAI, Claude, Gemini) Experience deploying cloud-native solutions using GCP and/or Azure. Solid understanding of API design, microservices, and software architecture patterns. Familiarity with version control systems (e.g., Git, Azure DevOps). Experience with Docker and Kubernetes. Demonstrated ability to build and scale AI/ML solutions from proof-of-concept to production.
Skills:
GenAI/LLM,AI/ML