Pre-screened and vetted in Texas.
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”
“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”
Mid-level AI Engineer specializing in Generative AI agents and LLM production systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Mid-level Generative AI Engineer specializing in LLMs, RAG, and prompt engineering
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps