Associate Principal, AI Engineering
US - California - San Diego - HQ, United States
USD 187K-281K Mid-level Full Time
Tasks
- Architect RAG systems
- Automate platform provisioning
- Build managed AI service integrations
- Build responsible AI frameworks
- Create design patterns and platform standards
- Create infrastructure as code
- Define reference architectures
- Deploy and monitor models
- Design API standards
- Design CI/CD pipelines
- Design cloud-native solutions
- Design event-driven architectures
- Design microservices
- Design multi-agent workflows
- Detect model drift
- Develop technology roadmaps
- Drive cross-functional delivery
- Enforce containerization standards
- Establish LLMOps practices
- Establish MLOps practices
- Establish prompt engineering standards
- Evaluate emerging AI technologies
- Implement evaluation pipelines
- Implement fallback and cost controls
- Integrate LLM providers
- Lead architectural reviews
- Manage trade offs with stakeholders
- Mentor engineering teams
- Orchestrate LLM workflows
- Provide technical leadership
- Represent architecture in executive forums
- Set content safety controls
- Set model governance
Perks/Benefits
Skills/Tech-stack
AWS | AlloyDB | Angular | Azure | BigQuery | CI/CD | Cloud Functions | Cloud platform | Content Safety | Databricks | Distributed Systems | Docker | Fine Tuning | Google Cloud | Google Cloud Platform | GraphQL | Java | JavaScript | Kafka | Kubernetes | LLMOps | Langchain | Langgraph | MLOps | Microservices | Model Governance | MySQL | Node.js | Observability | Oracle | PGVector | Pinecone | PostgreSQL | Prompt engineering | Pub/Sub | Python | RAG | REST | React | SQL | SQL Server | Snowflake | Spring Boot | Spring Cloud | Terraform | Vector Databases | Vector Search | Vertex AI | Weaviate
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Architect | AI Engineer | Architect | Engineer | Senior AI Engineer
Regions
Countries
States
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