ClifyX
Posted 69 days agoVerified live 1d ago
AI Engineer
Brief overview
Remote
Prompt EngineeringChain-of-Thought PromptingStructured Output DesignAgentic Application DevelopmentTool-CallingMulti-Step Workflow DesignMulti-Agent OrchestrationLangChainAutoGenLLM API IntegrationRetrieval-Augmented Generation (RAG) PipelinesVector DatabasesEmbeddingsAI Solution Architecture
About the company
ClifyXclifyx.com
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations.
Job description
Summary
ClifyX is a company focused on AI solutions, and they are seeking an AI Engineer to build and develop LLM-powered applications. The role involves integrating APIs, evaluating workflows, and translating business use cases into scalable AI solutions.
Responsibilities
- Build LLM-powered applications with strong prompt engineering skills (few-shot, chain-of-thought, structured outputs)
- Develop agentic applications — tool-calling, multi-step workflows, multi-agent orchestration (LangChain, AutoGen, etc.)
- Integrate LLM APIs and RAG pipelines (vector DBs, embeddings) into production systems
- Evaluate and iterate on prompts/workflows for quality, cost, and latency
- Translate business use cases into scalable AI solutions, staying current with LLM tooling
Skills
- Build LLM-powered applications with strong prompt engineering skills (few-shot, chain-of-thought, structured outputs)
- Develop agentic applications — tool-calling, multi-step workflows, multi-agent orchestration (LangChain, AutoGen, etc.)
- Integrate LLM APIs and RAG pipelines (vector DBs, embeddings) into production systems
- Evaluate and iterate on prompts/workflows for quality, cost, and latency
- Translate business use cases into scalable AI solutions, staying current with LLM tooling
Qualifications
Must Haves
- Build LLM-powered applications with strong prompt engineering skills (few-shot, chain-of-thought, structured outputs)
- Develop agentic applications — tool-calling, multi-step workflows, multi-agent orchestration (LangChain, AutoGen, etc.)
- Integrate LLM APIs and RAG pipelines (vector DBs, embeddings) into production systems
- Evaluate and iterate on prompts/workflows for quality, cost, and latency
- Translate business use cases into scalable AI solutions, staying current with LLM tooling
