Team Lead – AI Engineering

Fetcherr experts in deep learning, 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.

We are looking for a skilled and hands-on Team Leader to build a new world by natural language. You’ll lead a team focused on building intuitive, conversational interfaces that let users explore, understand, and interact with cogeneration of data-driven applications complex business data. If you’re passionate about solving real-world challenges through smart, scalable AI systems — we want to hear from you.

This isn’t just a people management role — it's an opportunity to lead high-impact development at the intersection of GenAI, data infrastructure, and product experience. You’ll design backend systems, drive applied AI use cases, and help shape how users access insights in real time.

Responsibilities:

• Lead and mentor a cross-functional team of engineers working on AI-driven data interfaces
• Design and build backend systems that connect natural language input to complex data pipelines
• Drive implementation of real-time analytics, visualizations, and diagnostics based on internal datasets
• Work closely with product managers to translate user needs into scalable technical solutions
• Ensure code quality, performance, and production readiness across the team
• Collaborate with data scientists, infra engineers, and client-facing teams to deliver end-to-end value
  
  

• 2+ years of experience in a leadership role, managing and mentoring technical teams
• Strong engineering background with hands-on coding skills in Python and/or TypeScript (Angular)
• Experience building scalable backend or data-centric applications
• Solid understanding of system design, testing, and development best practices
• Great communication skills and ability to lead through collaboration and clarity
• Motivation to explore the intersection of AI, data, and product
  
  

• Practical experience with Generative AI technologies (e.g., OpenAI, HuggingFace, Claude, etc.)
• Familiarity with cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines
• Degree in Computer Science or a related quantitative field
• GenAI experience is a plus, but not a requirement for strong engineering candidates