Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.
As VP Engineering, 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.
Responsibilities:
Strategic & Technical Leadership
- Act as a senior technical authority in data architecture, analytics, monitoring, and system design.
- Report to the CTO and collaborate with Sr. peers to define and execute the company’s technical roadmap.
- Drive execution, innovation, process improvement, and change management across engineering and data science teams.
- Scale the R&D team in line with Fetcherr’s rapid growth.
- Drive the effective usage of state of the art AI tools for improving productivity and scaling the team capabilities.
Engineering & Operational Excellence
- Design and refine engineering processes to improve reliability, velocity, and quality.
- Champion data quality, validation, and analytics engineering practices.
- Deliver the commitments according to customer requirements and timelines.
- Drive productivity and quality, also through the best practice leverage of AI tools and agentic coding.
Customer & Product Alignment
- Serve as a technical interface to product management, understanding the customer needs and translating them into product development execution and technical strategies.
- Represent R&D in customer discussions, guiding prioritization and product development with a real-world impact lens.
People & Culture
- Lead a local team while collaborating with remote and distributed teams, fostering alignment, engagement, and accountability.
- Promote a collaborative, analytical and data driven, hands-on culture across engineering, data science, and product.
- Partner closely with product and data stakeholders to deliver scalable, production-grade AI solutions.