Principal AI Engineer
Tasks
- Architect RAG systems
- Build agent harnesses and reusable skills tools
- Build event driven pipelines for agent orchestration
- Design and ship multi agent systems
- Embed Responsible AI practices
- Make build buy decisions balancing reliability latency security and cost
- Own architecture for generative and agentic AI
- Productize agents with guardrails and evaluation
- Run design and code reviews and mentor engineers
- Set architecture and code quality standards
- Use AI coding tools for development
Perks/Benefits
Skills/Tech-stack
AWS | Agent Orchestration | Agentic loops | Auditability | Autogen | Azure | Bias Mitigation | Circuit Breakers | Context engineering | CrewAI | Embeddings | Evaluation harnesses | Event Driven | Event-driven architecture | Function Calling | GCP | Go | GraphRAG | Guardrails | Human-in-the-loop | Java | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | MCP servers | MLOps | Memory systems | Multi-Agent | Multi-agent orchestration | Observability | OpenTelemetry | Privacy | Prompt engineering | Python | Responsible AI | Retrieval-Augmented Generation | The Loop | Tool/function calling | Tracing | TypeScript | Vector Databases
Education
Roles
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