AI/ML Engineer - Need Locals

Overview

On Site
Full Time
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - Long Term

Skills

GCP
AI
LangChain
Vertex AI
AI/ML
MLOps

Job Details

Role: AI Engineer Agent Development, MLOps & UI (Google Cloud Platform Vertex AI + LangChain)

Location: Atlanta, GA (Hybrid) - Need Locals or Nearby

Job Summary:

We are seeking a hands-on AI Engineer to design, build, and deploy intelligent AI agents using Google Cloud Platform 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 Google Cloud Platform 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 Google Cloud Platform 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, Google Cloud Platform 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.