Lead Data Scientist

Job Title: Lead Data Scientist Location: Raleigh, NCWork Model: Hybrid - 3 days onsite / 2 days remote About the Role We are looking for a hands-on Data Scientist to design, build, and deploy production-grade Generative AI systems on AWS.This role goes beyond experimentation"”you will architect secure, scalable, and costefficient GenAI solutions used by real users in enterprise environments.You will work closely with engineering, data, and product teams to deliver LLM-powered applications, including RAG-based document intelligence, chatbots, and AI assistantsKey Responsibilities Architect and implement Generative AI solutions using LLMs (GPT, Claude, Mixtral, etc.)Design and deploy Retrieval-Augmented Generation (RAG) pipelines for document Q&A and enterprise searchBuild semantic search and embedding pipelines using vector databases (FAISS, OpenSearch, Pinecone)Select and optimize LLM models, prompts, and inference strategies for accuracy, latency, and costImplement hallucination mitigation techniques (grounding, prompt constraints, validation layers)Design secure, scalable architectures on AWS (Bedrock, SageMaker, Lambda, API Gateway, S3)Fine-tune models using PEFT techniques (LoRA, QLoRA) when requiredPartner with MLOps teams to productionize models with CI/CD, monitoring, and rollbackOptimize GenAI systems for cost, latency, and throughputCollaborate onsite with cross-functional teams (3 days/week in Raleigh)Required Skills & Experience Generative AI & LLMs Strong understanding of LLM architectures and inferenceHands-on experience with RAG systems in productionPrompt engineering, temperature/top-p tuningKnowledge of LoRA / QLoRA / PEFT techniquesExperience mitigating hallucinations and improving factualityEmbeddings & Retrieval Chunking strategies and metadata handlingSemantic embeddings (Sentence-BERT, OpenAI, etc.)Vector similarity search (cosine, dot-product)Vector databases: FAISS, OpenSearch, Pinecone AWS & Cloud Architecture AWS AI/ML services: Bedrock, SageMakerServerless & APIs: Lambda, API GatewayData storage: S3, DynamoDBSecurity: IAM, KMS, VPC, CloudTrailExperience designing enterprise-grade, compliant systems Programming & Frameworks Python (strong)Experience with LangChain, Haystack, FastAPI (or similar)Familiarity with async processing and caching layersMLOps & Production Model versioning and monitoringCI/CD for ML systemsRollback strategies and drift detectionPerformance and cost monitoringQualifications 7+ years in data science, software/ML engineering, with 2+ years in GenAI/LLMsProven experience deploying AI systems to production

Created: 2026-05-12