Principal AI Engineer
Tasks
- Apply test-driven development
- Bridge technical and non-technical stakeholders
- Build reusable AI tooling
- Champion AI-assisted development practices
- Codify engineering baselines
- Conduct evaluation and production readiness
- Define AI deployment patterns
- Deploy models to public cloud
- Design AI productization playbook
- Design multi tenant AI services
- Enforce data boundary controls
- Establish AI agent governance
- Integrate LLMs
- Mentor engineers and tech leads
- Operate multi tenant microservices
- Own AI governance policies
- Partner on AI security and compliance
- Perform AI threat modeling
- Serve as technical authority for AI ML
Perks/Benefits
Skills/Tech-stack
AWS | Artificial Intelligence | Boundary enforcement | CI/CD | Cloud platform | Data Boundary Enforcement | Data Classification | Docker | Evaluation Frameworks | Google Cloud | Google Cloud Platform | Human-in-the-loop | ISO 27001 | Infrastructure as Code | Kubernetes | LLM integration | Language Models | Large Language Models | Machine Learning | Microservices | Microsoft Azure | Multi-tenancy | Prompt injection | Python | SOC2 | Terraform | Test-Driven | Test-Driven Development | The Loop | Threat modeling | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Principal | Principal AI Engineer
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