AI Engineer - RapidCanvas

David Joseph & Company
Austin, United States of America
11 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 200K

Job location

Remote
Austin, United States of America

Tech stack

API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Azure
Big Data
Cloud Computing
Python
Machine Learning
NoSQL
Software Deployment
SQL Databases
Feature Engineering
Data Ingestion
System Availability
Flask
Large Language Models
Spark
Deep Learning
FastAPI
Containerization
Kubernetes
Information Technology
XGBoost
Dask
Machine Learning Operations
Front End Software Development
Api Design
Docker

Job 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

Requirements

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

Benefits & conditions

  • Health, dental, and vision insurance
  • Outcome-oriented flexibility - focus on impact over hours logged

About the company

RapidCanvas is an enterprise AI company based in Austin, Texas, founded in 2021. The company offers a hybrid AI platform that integrates autonomous AI agents with human expertise, allowing businesses to build, deploy, and scale custom AI solutions significantly faster and at lower cost than traditional methods. The no-code platform supports full-lifecycle AI including data integration, predictive analytics, and workflow automation. Series A with $39.5M raised, serving manufacturing, retail, and financial services customers globally.

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