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Agentic AI Engineer
Agentic AI Engineer
This role involves building and managing the logic for complex multi-agent workflows, designing systems for user onboarding, dynamic scenario creation, and real-time interactive simulation loops. The engineer will also be responsible for architecting state management for LLMs to prevent context rot and hallucination, and for designing and implementing an evaluations framework for prompt performance and agent lifecycles.
About the role
Responsibilities
- Agent Design & Orchestration: Build and manage the logic for complex multi-agent workflows. You will design the systems that handle user onboarding (profile generation), dynamic scenario creation, and real-time interactive simulation loops.
- Context Engineering: Architect state management for the LLMs to prevent "context rot" and hallucination. You will strictly govern what each agent knows, structuring context dynamically to maximize token caching and minimize latency.
- Advanced Prompting & Evals Infrastructure: Write, test, and version-control robust system instructions for standalone LLMs and multi-agent workflows. You will design, implement, and own a rigorous evaluations (evals) framework to programmatically score both individual prompt performance and end-to-end agent lifecycles. You will establish the CI/CD-style testing loops required to iterate on model behavior predictably and safely at scale.
- Moderation and Security Risk Mitigation: Design and implement pipelines in collaboration with our backend team that moderate harmful or offensive user inputs while also mitigating prompt injection attacks and undesired LLM outputs.
- Full-Stack Integration: Work closely with backend and frontend teams to seamlessly integrate AI outputs into the user interface, ensuring smooth data flow from the models down to the client.