Senior AI Engineer – LLM / Agents
Tasks
- Build evaluation frameworks
- Convert workflows into measurable agent systems
- Create reusable templates and scorecards
- Create standards for skills and tools
- Define agent workflow architecture
- Design observability for agents
- Establish reusable workflow patterns
- Identify failure modes and improve tests and instrumentation
- Manage tokens and context
- Mentor engineers on eval driven development
- Partner on MCP servers and platform governance
- Review workflows before production release
Perks/Benefits
- 401k match
- Flexible work arrangements
- Health and wellness benefits
- Hybrid office setup
- Life insurance
- Paid Holidays
- Paid device support
- Paid parental leave
- Paid time off
- Reimbursement for phone internet and data
- Wellness support
Skills/Tech-stack
API Integration | Application design | Audit Logging | Azure | CI/CD | ChatGPT enterprise | Cloud Platforms | Context Management | Cost Optimization | Data Pipelines | Databricks | Evaluation Frameworks | LLM orchestration | Language Models | Large Language Models | Latency optimization | Logging | MCP | Machine Learning | Microsoft Teams | Monitoring | Observability | OpenAI | Prompt engineering | Python | RBAC | RBAC Permissions | RBAC Secrets | RBAC Security | Retrieval-Augmented Generation | Secure Application Design | Secure application | SharePoint | Structured Output | Token Management | Tool-Calling
Education
Roles
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