Staff Enterprise AI Engineer - Agentic Workflows & Productivity
Tasks
- Build and operate model infrastructure and cost monitoring
- Build cross platform agent interoperability with schema mapping
- Build reference agents RAG pipelines integrations and MCP connectors
- Debug non deterministic retrieval and generation behavior
- Design and deliver agent factory patterns and templates
- Enable adoption of AI capabilities with training and support
- Establish evaluation quality and monitoring for agent workflows
- Harden platform foundations with security and observability
- Lead agent workflows across ideation development and deployment
- Lead technical strategy standards patterns and guardrails for RAG security and governance
- Mentor engineers through code review pairing and design reviews
- Own enterprise AI platform architecture and rollout
- Steer external delivery partners scope review and timeline
Perks/Benefits
Skills/Tech-stack
A2A protocols | API Integration | Agent Orchestration | Agentic Systems | Authentication | Authentication and Identity | Authentication and Identity Federation | CD | CI | CI/CD | Confluence | Cost Optimization | Data Privacy | Eval Pipelines | Figma | Function Calling | Gemini | GitHub | IAM | Identity Federation | JavaScript | Jira | LLM | MCP | Machine Learning | Model Evaluation | Model Monitoring | Model cost | Model cost optimization | Multi Model Fallback | Multi-model | NotebookLM | OAuth | OAuth 2 | OAuth 2 0 | Observability | Prompt Eval Pipelines | Prompt engineering | Python | RAG | Routing | SSO | Security Compliance | Tenant Isolation | Tool-Calling | Vertex AI | Workload Identity
Education
N/A
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