Staff GenAI Engineer
Tasks
- Build LLM systems
- Build microservices
- Control cloud costs
- Create Design Docs
- Define cloud deployment strategy
- Deploy on AWS Azure and GCP
- Deploy on Kubernetes
- Design agentic workflows
- Design data pipelines
- Design tool calling
- Develop AI APIs
- Develop GenAI production systems
- Ensure production readiness
- Implement RAG architecture
- Implement memory management
- Implement monitoring and logging
- Implement security practices
- Lead backend architecture
- Lead incident prioritization
- Manage NoSQL databases
- Manage SQL databases
- Mentor engineers
- Optimize performance
- Orchestrate AI pipelines
- Plan migrations
- Standardize container deployments with Docker
- Train fine tune evaluate deploy ML models
Perks/Benefits
Skills/Tech-stack
AWS | Agentic Workflows | Azure | CI/CD | Data Pipelines | Distributed Systems | Docker | Fine Tuning | GCP | Generative AI | Kubernetes | Language Models | Language Processing | Large Language Models | Logging | Machine Learning | Microservices | Model Evaluation | Model Fine-tuning | Model Training | MongoDB | Monitoring | Natural Language | Natural Language Processing | NoSQL | PostgreSQL | Python | RAG | SQL | Security | Terraform
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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