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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - RapidCanvas - **Company:** David Joseph & Company - **Location:** Austin, TX, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Python (Programming Language), Machine Learning, NoSQL, Software Deployment, SQL Databases, Feature Engineering, Data Ingestion, System Availability, Flask (Web Framework), Large Language Models, Apache Spark, Deep Learning, Fastapi, Containerization, Kubernetes, Information Technology, Xgboost, Dask, Machine Learning Operations, Front End Software Development, Api Design, Docker - **Published:** June 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=82825a4b70114e5d ## About the Role Do you have experience in SQL?, Do you have a Master's degree?, * 5+ years of professional experience moving ML models into production environments * Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related quantitative field * Proven experience implementing LLMs and RAG architectures using LangChain, LlamaIndex, OpenAI APIs, or similar * Advanced Python proficiency including FastAPI or Flask for model serving * Hands-on experience with vector databases - Pinecone, Milvus, Weaviate, or equivalent * MLOps experience - Docker, Kubernetes, MLflow, Airflow, or similar for full ML lifecycle management * Cloud platform experience - AWS, GCP, or Azure * Experience with SQL/NoSQL databases and large-scale data processing * US Citizen or Green Card holder - no visa sponsorship available, * Experience with Auto-ML or No-Code/Low-Code data science platforms * Proficiency with gradient-boosted trees (XGBoost, LightGBM), time-series forecasting, and deep learning frameworks * Experience with automated feature engineering and hyperparameter tuning (Optuna, Ray Tune) * Familiarity with Spark or Dask for large-scale data processing * Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field, * First-round team interview - technical and collaborative session * Technical assessment - practical skills evaluation or take-home assignment * Deep-dive interview - architecture, methodologies, and project experience * Cultural alignment and leadership interview with key stakeholders ## Description As an AI Engineer at RapidCanvas, you will design, train, and deploy machine learning models and LLM-powered systems that power an automated machine learning platform for enterprise users. You will bridge the gap between complex data science and intuitive user experiences - owning everything from RAG pipeline architecture to production deployment and API development., * Design, train, and optimize ML models and LLMs to solve complex predictive and generative tasks within the RapidCanvas platform * Architect and implement robust RAG workflows - vector database management, embedding optimization, and advanced prompt engineering * Deploy scalable AI services using containerization and orchestration tools, ensuring high availability and low-latency inference * Build and maintain automated data ingestion and preprocessing pipelines to transform raw enterprise data into high-quality training sets and feature stores * Establish rigorous evaluation frameworks to measure model accuracy, drift, and computational efficiency * Develop secure, high-performance APIs to expose AI capabilities to the frontend ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)