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AI Agent Engineer / LLM Application Engineer (RP - 03112026)

Role overview

Qualifications

  • Proven experience building LLM-powered applications or AI agents
  • Strong experience with Retrieval-Augmented Generation (RAG) architectures
  • Proficiency in Python and AI/ML frameworks, with familiarity in vector databases and semantic search
  • Experience with LLM APIs (e.g., OpenAI, Anthropic) and integrating AI solutions with APIs, databases, and cloud services

Responsibilities

  • Design, develop, and deploy AI agents and LLM-powered applications for business use cases, including RAG pipelines for knowledge retrieval and contextual responses
  • Build and optimize RAG pipelines and semantic search with vector databases; connect LLM apps to databases, APIs, and cloud services
  • Develop NLP-based systems for text processing and conversational AI, and implement Voice AI systems for speech recognition and automated call workflows
  • Fine-tune prompts, monitor performance, document architectures and deployment processes, and collaborate with cross-functional teams to translate requirements into AI solutions

About the company

RippedBoxStation logo

RippedBoxStation

is a company that deliver great user experience by deeply understanding what people want and love. Then deliver the features, messages, and content that are most helpful, relevant and timely. That’s what makes users happy and loyal. Ripped Box Station strives to deliver the tools and support that helps companies deliver that great experience.

Company details

Company typeStartup
Company size11 - 50

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Job description

Position: AI Agent Engineer / LLM Application Engineer

Number of hours: TBC

Schedule: TBC

Key Responsibilities

  • Design, develop, and deploy AI agents and LLM-powered applications for various business use cases

  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval and contextual responses

  • Develop NLP-based systems for text processing, classification, and conversational AI

  • Integrate Voice AI systems for speech recognition, voice assistants, and automated call workflows

  • Connect LLM applications with databases, APIs, and external systems

  • Fine-tune prompts, optimize model performance, and improve response accuracy

  • Implement automation workflows using AI agents and orchestration frameworks

  • Monitor, test, and continuously improve AI system performance and reliability

  • Document AI architectures, workflows, and deployment processes

  • Collaborate with cross-functional teams to translate business requirements into AI-driven solutions

Qualifications

  • Proven experience building LLM-powered applications or AI agents

  • Strong experience with Retrieval-Augmented Generation (RAG) architectures

  • Solid background in Natural Language Processing (NLP)

  • Experience developing Voice AI systems or conversational AI solutions

  • Proficiency in Python and working with AI/ML frameworks

  • Experience with LLM APIs (e.g., OpenAI, Anthropic, or similar platforms)

  • Familiarity with vector databases, embeddings, and semantic search

  • Experience integrating AI solutions with APIs, databases, and cloud services

  • Strong analytical and problem-solving skills

  • Ability to work independently and communicate technical concepts clearly



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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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