Data Scientist

Interview: VirtualUSC, GC and GC EADRemote : non local to AtlantaJD:Document Intelligence: Extracting and analyzing large volumes of corporate documents using NLP and AIConversational AI: Building enterprise chat systems for knowledge discovery and decision supportGenAI & LLMs: Developing, optimizing, and monitoring LLM and RAG pipelinesEnterprise Integration: Integrating AI solutions with corporate systems (OAuth, LDAP, cloud services)Scalable Platforms: Designing microservices-based, production-ready AI solutionsKey ResponsibilitiesEnhance and maintain an enterprise AI chat and document intelligence platformDevelop and optimize RAG pipelines and LLM integrationsBuild backend APIs and AI tools for scalable, multi-team useCollaborate with business teams to translate document and data needs into AI solutionsSupport production deployments with monitoring, logging, and performance optimizationCore TechnologiesLanguages: Python, JavaScript/TypeScriptAI/ML: LLMs (Claude, GPT), LangChain, vector search, NLP librariesBackend: FastAPI, Node.js, ExpressCloud & DevOps: AWS (ECS, EKS, S3, Lambda, Bedrock), Docker, Kubernetes, CI/CDDatabases: MongoDB, vector databasesRequired QualificationsBachelor's degree in Computer Science, Data Science, ML, Linguistics, or related field2+ years of experience in NLP, AI, or LLM-based developmentStrong experience building APIs and production AI systemsFamiliarity with RAG architectures, embeddings, and semantic searchExperience deploying AI solutions in cloud environmentsPreferred QualificationsMaster's or PhD in a related fieldExperience with MLOps, microservices, and enterprise authentication systemsKnowledge of advanced NLP techniques and observability tooling