Data Scientist/Agentic AIML/AI-ML Engineer-(USC)(GC)-W2 Only

Job Description We are seeking a Senior Data Scientist / Agentic AI-ML Engineer with 11+ years of experience in building enterprise AI, Machine Learning, and Generative AI solutions. The ideal candidate should have strong expertise in LLMs, Agentic AI, RAG, LangChain/LangGraph, Python, FastAPI, Azure OpenAI, AWS, and cloud-native AI architectures. We are seeking a Senior Data Scientist / Agentic AI-ML Engineer with 11+ years of experience in building enterprise AI, Machine Learning, and Generative AI solutions. The ideal candidate should have strong expertise in LLMs, Agentic AI, RAG, LangChain/LangGraph, Python, FastAPI, Azure OpenAI, AWS, and cloud-native AI architectures. Required Skills 11+ years in AI/ML, Data Science, and Predictive Analytics Strong Python, SQL, Scikit-learn, TensorFlow, PyTorch Hands-on with GPT-4, Claude, Gemini, Llama, LangChain, LangGraph, CrewAI, AWS Bedrock Experience building RAG applications, vector databases (Pinecone, FAISS, ChromaDB, pgvector), and semantic search NLP expertise with Hugging Face, spaCy, NLTK, embeddings, prompt engineering Cloud experience with AWS, Azure, and Google Cloud Platform MLOps using Docker, Kubernetes, MLflow, Kubeflow, CI/CD Big Data technologies including Spark, Kafka, Databricks Experience with FastAPI, REST APIs, AI solution architecture, and enterprise AI platforms Preferred domain experience in Telecom, Banking, Healthcare, Retail, or E-Commerce Mandatory Submission Requirements Senior Data Scientist / Agentic AI-ML Engineer with 11+ years of experience delivering end-to-end AI, Machine Learning, and Generative AI solutions across Telecom, Banking, Healthcare, E-commerce, and Retail domains. Currently contributing to Next-Gen AI initiatives within the Veloce platform at T-Mobile, exploring and prototyping AI/ML and Generative AI capabilities to enhance automation, knowledge retrieval, and decision support across telecom workflows. Extensive expertise in Python, Azure OpenAI, AWS, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, LangGraph, FastAPI, Predictive Analytics, Intelligent Automation, AI Solution Design, and Enterprise AI Platforms, delivering scalable cloud-native AI solutions. Hands‑on experience developing Machine Learning models such as BOM ancillary prediction systems, leveraging historical telecom deployment data to automate component recommendations and improve operational efficiency. Designed and implemented Generative AI solutions including Retrieval‑Augmented Generation (RAG) chatbots to retrieve enterprise knowledge from Confluence documentation using LLMs, embeddings, and vector search. Strong expertise in LLM integration and GenAI frameworks including LangChain, LangGraph, CrewAI, and AWS Bedrock, enabling conversational AI assistants and intelligent enterprise knowledge systems. Skilled in RAG architecture design, vector embedding pipelines, and semantic search systems using vector databases such as ChromaDB, pgvector, FAISS, and Pinecone. Proficient in Python-based AI stack including Pandas, NumPy, Scikit-learn, FastAPI, and modern AI frameworks for building scalable AI services and backend APIs. Experience designing cloud-native AI architectures and MLOps pipelines using AWS, Azure, and Google Cloud Platform, integrating CI/CD, containerization, and infrastructure automation. Strong background in NLP and text analytics, including named entity recognition, sentiment analysis, topic modeling, summarization, embeddings, and enterprise knowledge retrieval systems. Demonstrated leadership in cross‑functional collaboration, AI solution architecture, and translating complex data insights into scalable enterprise AI systems Technical Skills Category Technologies / Tools Programming Languages Python, R, SQL, JavaScript ML / DL Frameworks Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost, LightGBM, CatBoost, FastText Generative AI / LLMs GPT-4, Gemini, Claude, LLaMA (2/3), Falcon, Mistral, BioBERT, ClinicalBERT, T5, BERT, LangChain, LangGraph NLP Tools spaCy, NLTK, Gensim, TextBlob, Hugging Face Transformers, Prompt Engineering, RAG Pipelines Graph & Multimodal AI Neo4j, NetworkX, DGL, PyG, GNNs, Vision Transformers (ViT), ResNet, EfficientNet, CLIP MLOps & Automation MLflow, Kubeflow, Airflow, Jenkins, GitLab CI/CD, Docker, Kubernetes, Terraform, Vertex AI, AWS SageMaker, Azure ML Cloud Platforms AWS (S3, EC2, SageMaker, Lambda, Glue, Redshift), Google Cloud Platform (Vertex AI, BigQuery, Dataflow), Azure (ML, Databricks, Cognitive Services) Vector Databases & Search FAISS, Pinecone, Weaviate, ElasticSearch, ChromaDB Big Data Ecosystem Apache Spark, Kafka, Hadoop, Hive, HBase, Cassandra, Databricks Data Visualization Tableau, Power BI, R Shiny, Plotly, Dash, Seaborn, Matplotlib Databases PostgreSQL, MySQL, Oracle, MongoDB, Cassandra Machine Learning Techniques Regression, Classification, Clustering (K-Means, DBSCAN), Reinforcement Learning (DQN, PPO), Anomaly Detection, Time Series (ARIMA, Prophet) Deep Learning Models CNN, RNN, LSTM, GANs, Autoencoders, Siamese Networks, Transformers Security & Compliance HIPAA, GDPR, PHI/PII Masking, IAM, OAuth 2.0, API Gateway, Responsible AI, SHAP, LIME Development Tools Jupyter Notebook, VSCode, PyCharm, Git, Apache NiFi, Jenkins Monitoring / Observability Prometheus, Grafana, CloudWatch, SageMaker Model Monitor #J-18808-Ljbffr iSite Technologies Corp.