AI Engineer
Tasks
- Build RAG architectures and agentic workflows
- Collaborate to translate prototypes into scalable solutions
- Create technical documentation for AI systems
- Deploy and monitor models in production
- Design and build production AI ML systems
- Develop AI infrastructure and services on cloud
- Develop and maintain MLOps pipelines
- Implement CI CD and model governance
- Integrate LLM applications into enterprise platforms
Perks/Benefits
- Access to latest AI tooling
- Collaborative low bureaucracy environment
- Encouragement to experiment and innovate
- Remote within Atlanta area
Skills/Tech-stack
AWS | Agentic AI | Autogen | Azure | CI/CD | Docker | GCP | Hugging Face | Infrastructure as Code | Keras | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Governance | OpenAI API | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | TensorFlow | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer
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