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

Roles & Responsibilities

  • 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

Requirements:

  • 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

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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