Full-Stack AI Engineer

**Job Title: Full\-Stack AI Engineer****Position Type:** Full\-Time, Remote **Working Hours:** U.S. client business hours (with flexibility for deployments, experimentation cycles, and sprint schedules) **About the Role** Our client is seeking a Full\-Stack AI Engineer to design, build, and deploy AI\-powered applications that bridge modern software engineering with applied machine learning. This role focuses on taking AI solutions from prototype to production — ensuring systems are scalable, reliable, secure, and optimized for real\-world business impact. The ideal candidate combines strong full\-stack engineering skills with hands\-on experience integrating LLMs, machine learning models, vector databases, and AI workflows into production environments. You will work closely with product, engineering, and data teams to build intelligent applications that improve automation, user experience, and operational efficiency. This is a highly technical, execution\-focused role for someone comfortable owning AI systems end\-to\-end — from infrastructure and APIs to front\-end experiences and deployment pipelines. **Responsibilities****AI Model Integration \& Deployment*** Deploy and integrate pre\-trained and fine\-tuned ML/LLM models using platforms such as OpenAI, Hugging Face, TensorFlow, and PyTorch * Build scalable inference APIs using FastAPI, Flask, Node.js, or similar frameworks * Implement vector search and retrieval systems using Pinecone, Weaviate, FAISS, or ChromaDB * Design and optimize Retrieval\-Augmented Generation (RAG) pipelines for AI\-powered applications * Monitor model accuracy, latency, and operational performance in production environments **Data Engineering \& AI Pipelines*** Build ETL pipelines for ingesting, cleaning, transforming, and processing structured and unstructured datasets * Automate data preprocessing, labeling, validation, and versioning workflows * Manage datasets and pipelines using Airflow, Prefect, Dagster, or similar orchestration tools * Store and manage datasets in cloud data warehouses such as BigQuery, Snowflake, or Redshift * Optimize pipelines for scalability, reliability, and cost efficiency **Full\-Stack Application Development*** Build front\-end interfaces in React, Next.js, or Vue for AI\-powered features such as chatbots, dashboards, search, and analytics tools * Develop scalable back\-end services and microservices that connect AI models to business logic * Ensure applications are responsive, secure, intuitive, and production\-ready * Design APIs and services that support high concurrency and scalable AI workloads **Infrastructure, DevOps \& Deployment*** Containerize services using Docker and deploy workloads to Kubernetes environments * Build and maintain CI/CD pipelines for application and model deployments * Monitor infrastructure health, inference latency, system uptime, and operational costs * Implement observability and monitoring using MLflow, Weights \& Biases, Datadog, Prometheus, or...