Principal AI Engineer
Tasks
- Build RAG systems
- Deploy multi agent workflows for engineering tasks
- Design agentic workflows
- Design scalable AI ML pipelines with LLMs and RAG
- Develop coding assistance and coding agents
- Develop reusable accelerators and reference architectures
- Ensure AI meets quality security scalability reliability standards
- Establish AI development best practices
- Generate verified pull requests with regression tests
- Implement AI testing and validation practices
- Integrate AI APIs into customer facing applications
- Integrate agents with error monitoring and bug reporting
- Lead AI adoption across engineering function
- Mentor engineers using AI tools
- Prototype and deploy AI powered solutions
- Refactor for modularity and deterministic testing
- Train engineers to define intent for AI agents
- Translate business problems into scalable architectures
- Translate product and business needs into technical solutions
Perks/Benefits
Skills/Tech-stack
Agent workflows | Agentic Frameworks | Agile | Artificial Intelligence | Azure | DevOps | Error Monitoring | Jira | LLM APIs | Language Models | Large Language Models | Machine Learning | Prompt engineering | Pull Request Automation | Pull request | RAG | Refactoring | Regression testing | Retrieval-Augmented Generation | Serverless | Software Security | Software reliability | Software scalability
Education
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
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