LLMOps Engineer
Tasks
- Build CI/CD pipelines for AI systems
- Build evaluation infrastructure for hallucination and tool call success
- Build sandboxed environments for AI agent repository access
- Create operational playbooks for incident recovery
- Define SLOs for AI system reliability
- Design AWS infrastructure for AI and agent systems
- Design and operate CodeAI development pipeline
- Design environment promotion and automated rollback
- Establish governance and security guardrails
- Handle deployments monitoring and incident response for AI systems
- Implement monitoring with AWS CloudWatch and evaluation dashboards
- Implement secure configuration and secrets management
- Implement versioning for models prompts and LangGraph agent graphs
- Manage integrations with Amazon Bedrock
- Monitor and optimize cost per request
Perks/Benefits
- 401k employer match
- Access to events
- Company holidays
- FSA eligibility
- Free lunch onsite
- HSA eligibility
- Medical, dental, and vision coverage
- Paid time off
- Parental leave
Skills/Tech-stack
AWS | AWS CloudWatch | Amazon Bedrock | CI/CD | Evaluation | Incident Response | Infrastructure as Code | Langgraph | MLOps | Machine Learning | Model versioning | Monitoring | Observability | Prompt engineering | SLO | Secrets management | “as-code”
Education
N/A
Roles
DevOps | DevOps Engineer | Engineer | LLMOps Engineer | MLOps Engineer
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