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# Junior Cloud Automation Engineer

- **Company:** OpenKyber LLC
- **Location:** United States (Remote available)
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Cloud Database, Information Engineering, Data Security, Monitoring of Systems, Python (Programming Language), Knowledge-Based Systems, Machine Learning, Google Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Scikit Learn, Data Analytics, Xgboost, Machine Learning Operations, Virtual Agents, GPT, Data Pipelines
- **Published:** May 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=5a899d3773f42581

## About the Role

Do you have experience in XGBoost?, Senior GenAI Data Scientist / AI Engineer (LLM, RAG, Agentic AI) Job Summary We are seeking a highly skilled GenAI Data Scientist / AI Engineer with strong expertise in Machine Learning, Generative AI, and Agentic AI systems . The ideal candidate will design, build, and deploy scalable AI/ML and GenAI solutions , including LLM-based applications, RAG pipelines, and intelligent AI agents , while ensuring performance, scalability, and business impact., * Machine Learning (MANDATORY) Strong experience with: XGBoost LightGBM Scikit-learn

 * Programming Python (mandatory)
 * Generative AI LLMs (GPT, Claude, etc.) Prompt engineering AI agents / Agentic workflows RAG Systems Vector databases Embeddings Retrieval pipelines
 * MLOps & Deployment Model deployment CI/CD pipelines MLflow / monitoring tools
 * Cloud Platforms AWS / Google Cloud Platform
 * Statistics & Analytics Strong statistical modeling Data analysis and interpretation

Experience Required

 * 8+ years of experience in: Data Science / Machine Learning
 * Hands-on experience in: Generative AI (intermediate level)

Preferred Skills

 * Experience with: LangChain / CrewAI / AutoGen Vector DBs (Pinecone, FAISS, etc.) Experience in: Agentic AI systems Exposure to: Real-world GenAI applications

## Description

Machine Learning & Data Science

 * Design, build, and deploy ML models using: XGBoost, LightGBM, Scikit-learn
 * Perform: Model training, validation, and optimization
 * Translate business problems into data-driven solutions

Generative AI & Agentic AI

 * Design and implement: LLM-based applications AI agents and workflows
 * Work with frameworks like: LangChain / LangGraph / CrewAI / AutoGen
 * Enable: Tool calling Task automation Multi-agent orchestration

RAG & Knowledge Systems

 * Build Retrieval-Augmented Generation (RAG) pipelines
 * Work with: Vector databases Embeddings
 * Develop knowledge-based AI systems

Model Deployment & MLOps

 * Deploy models into production environments
 * Implement: CI/CD pipelines MLflow / model monitoring
 * Ensure: Model performance Scalability Reliability

Cloud & Data Engineering

 * Work on cloud platforms: AWS / Google Cloud Platform
 * Build scalable data pipelines and ML workflows

Monitoring & Optimization

 * Monitor: Model performance Data drift
 * Continuously improve models and pipelines

Security & Compliance

 * Ensure: Data security Compliance standards
 * Implement governance for AI systems

Collaboration & Communication

 * Engage with: Business stakeholders Engineering teams
 * Translate business requirements into AI solutions
 * Communicate model insights clearly


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