AI Engineer
AI Engineer
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Job Description
Job Title: AI Engineer
Must have SKills : Agent Development MLOps & UI (GCP Vertex AI LangChain)
Location: Atlanta GA ( 3 days in Office )
Duration: 6-12 Months Contract
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.
Employment Type
Full-time
