Fetcherr experts in deep learning, algo-trading, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

As Director of R&D, you will serve as a senior technical and organizational leader, helping to scale Fetcherr's data-driven products and engineering capabilities. This is a hybrid role combining technical authority, strategic vision, and operational excellence. You will co-lead the R&D organization, work directly with customers, and be instrumental in shaping cross-functional, product-focused engineering teams.

We’re looking for a leader who’s both visionary and hands-on, able to drive execution, foster innovation, and build high-performance engineering cultures at scale.

As Director of R&D – LLM Systems, you will lead the development of Fetcherr’s new LLM-based product from scratch. This role is a unique blend of technical leadership, product vision, and cross-functional execution.

You’ll manage a multidisciplinary team of AI engineers, backend developers, and data experts to design, prototype, and productionize a conversational analytics system powered by large language models (LLMs). Your team will own everything from RAG (retrieval-augmented generation) pipelines and prompt engineering, to visualization generation and reliability infrastructure.

This is a hands-on leadership role for someone excited to build one of the core AI pillars of Fetcherr’s future.

Responsibilities:

Vision & Strategy

• Define and lead the roadmap for Fetcherr’s LLM-based virtual analyst system.
• Translate high-level business and product goals into technical milestones and deliverables.
• Evaluate trade-offs between open-source and commercial LLM platforms (e.g., OpenAI, Claude, Gemini).
  
  

Team Leadership

• Build and lead a cross-functional R&D team (LLM engineers, software engineers, data engineers, QA).
• Establish a rapid experimentation-to-production pipeline for LLM-based features.
• Foster a culture of innovation, quality, and ownership.
  
  

System Design & Technical Execution

• Architect systems that combine LLMs, structured data, vector databases, and visualization libraries.
• Oversee development of:
• Prompt engineering and chaining
• RAG pipelines
• Natural language to SQL/query translation
• Auto-generated dashboards or visual responses (graphs, tables, charts)
• Ensure the system is scalable, cost-efficient, observable, and secure.
  
  

Collaboration & Impact

• Work closely with stakeholders across Product, Data, Engineering, and Customer teams.
• Prototype real use cases, test with users, and drive measurable business value.
• Serve as the internal champion for Fetcherr’s LLM capabilities.
  
  

Requirements:

You’ll be a great fit if…

Leadership & Execution

• 3+ years in a Director, Head of R&D, or AI Platform Lead role.
• Experience building or leading AI/LLM or NLP product teams.
• Proven ability to deliver from 0→1 in complex, AI-based systems.
  
  

Technical Depth

• Strong knowledge of LLM application architecture, including:
• Prompt engineering and retrieval-augmented generation (RAG)
• Vector databases, embeddings, and context injection
• Data-to-text generation and visualization tools
• Deep understanding of Python, cloud infrastructure (preferably GCP), and backend systems.
• Experience with LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face) and APIs (OpenAI, Claude, Gemini).
  
  

Communication & Product Thinking

• Excellent communication skills, in English, both written and verbal.
• Strong ability to align technical teams and product stakeholders.
• Deep curiosity about how to make complex data accessible through natural language.
  
  

Nice to Have:

• Experience with analytics platforms, BI, or natural language interfaces to data.
• Familiarity with multi-agent LLM systems or tool-augmented AI workflows.
• Background in airline, pricing, or financial domains.