Technical skills
ReactPythonData scienceSREQuality Assurance
Job Responsibilities
- Building AI search agents- including ReAct, planning, and multi-agent architectures via custom implementation or frameworks like LangGraph, Dify, or CrewAI.
- Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using Opensearch.
- Operating and monitoring vector/hybrid indexes (e.g. OpenSearch) in production environments.
- Implement grounding and citation to link generated answers back to their exact source passages.
- Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to continuously measure accuracy and detect drift.
- Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 3+ years of experience in developing AI systems, with a focus on retrieval-augmented generation (RAG).
- Proven track record in building and optimizing end-to-end RAG pipelines.
- Experience with AI search agent development using frameworks like ReAct, LangGraph, Dify, or CrewAI.
- Hands-on experience with OpenSearch or similar vector search technologies.
- Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow).
- Strong understanding of data ingestion, chunking, embeddings, and hybrid vector search techniques.
- Experience with monitoring and managing production environments.
- Knowledge of grounding and citation techniques in AI-generated content.
- Familiarity with synthetic QA datasets and evaluation metrics.