AI Engineer – Agent Development, MLOps & UI (GCP Vertex AI + LangChain)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer specializing in Agent Development, MLOps, and UI, based in Atlanta, GA, for a 3–6 month contract at a pay rate of "X". Key skills include GCP Vertex AI, LangChain, and Python programming.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
August 8, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Atlanta, GA
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🧠 - Skills detailed
#Terraform #MLflow #Programming #Scala #Consulting #Databases #Cloud #Python #Airflow #Streamlit #GCP (Google Cloud Platform) #DevOps #ML (Machine Learning) #Langchain #Docker #Deployment #Flask #AI (Artificial Intelligence) #FastAPI
Role description
Job Title: AI Engineer – Agent Development, MLOps & UI (GCP Vertex AI + LangChain) Location: Atlanta, GA (3 days in Office) Please don't apply for this position if you aren't willing to appear for the interview ons-site About Us: CirrusLabs is a leading consulting firm based in Alpharetta, GA, specializing in delivering innovative technical solutions to clients across various industries. We are committed to excellence, agility, and exceeding customer expectations. Job Summary: We are seeking a hands-on AI Engineer to design, build, and deploy intelligent AI agents using GCP Vertex AI, LangChain, and modern UI tools like Streamlit. The ideal candidate will bring together skills in large language models (LLMs), agent orchestration, MLOps, and user-friendly interface development to create powerful and accessible AI solutions. Key Responsibilities: • Design and implement LLM-based agents using LangChain, integrated with GCP Vertex AI services. • Build interactive UIs using Streamlit or similar frameworks to showcase and test AI agent capabilities. • Develop end-to-end ML pipelines for training, evaluation, and deployment using tools like Vertex Pipelines, Kubeflow, or Airflow. • Integrate with APIs, vector databases, and knowledge sources to enable RAG (Retrieval-Augmented Generation)workflows. • Deploy scalable, secure AI services using CI/CD pipelines, infrastructure-as-code, and version-controlled model registries. • Monitor model performance, manage experiments, and optimize agent behavior in production environments. • Work cross-functionally with product, design, and engineering teams to deliver intuitive, high-impact AI-powered applications. Required Qualifications: • 3–6 years of hands-on experience in AI/ML engineering, including recent work with LLMs and LangChain. • Proficiency with GCP Vertex AI tools such as Pipelines, Model Registry, Training, and Endpoints. • Strong Python programming skills, with experience in FastAPI, Flask, or similar web frameworks. • Demonstrated experience building interactive dashboards or tools using Streamlit, Gradio, or Dash. • Knowledge of MLOps workflows, including tools like MLflow, Weights & Biases, or Vertex AI Experiments. • Experience working with vector stores (e.g., FAISS, Pinecone, Weaviate) in agent pipelines. • Familiarity with retrieval-based QA, embeddings, and prompt engineering techniques. • Experience with LangGraph or similar agent orchestration frameworks. Preferred Qualifications: • Familiarity with cloud-native deployment and DevOps tools (Terraform, Docker, GCP Cloud Build). • Background in UX/UI design thinking or rapid prototyping for AI-driven applications. • Experience integrating LLMs with external APIs or private knowledge sources.