- Design and implement agentic architectures using frameworks such as LangGraph, Langchain, CrewAI, OpenCLAW, or similar.
- Build multi-agent workflows that coordinate tasks and reasoning across different tools.
- Develop systems that combine RAG, structured tools, and reasoning chains.
AI System Engineering
- Build and maintain multi-tenant AI infrastructure for scalable production systems.
- Implement caching strategies for AI calls to optimize performance and cost.
- Design LLM cost optimization strategies across prompts, models, and workflows.
Reliability & Observability
- Build observability and monitoring systems for AI pipelines.
- Implement response evaluation frameworks to measure AI output quality.
- Track and detect system failures, hallucinations, and degradation over time.
AI Infrastructure
- Work with vector databases, RAG pipelines, and context engineering techniques.
- Design scalable agent orchestration pipelines.
- Integrate AI agents with APIs, tools, and external services.
Frontend & Product Collaboration
- Work with React-based interfaces for AI-powered applications.
- Provide input on AI product UX/UI design.
- Collaborate with product and engineering teams to build usable AI systems.
Required Skills
AI Systems & Architecture
- Solid understanding of Agentic Architecture
- Hands-on experience building LLM-powered agents
- Deep knowledge of agent frameworks such as
- LangGraph
- CrewAI
- OpenCLAW
- or similar orchestration systems