System architect

Description

Fetcherr experts in deep learning, algo, 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 System Architect at Fetcher, you’ll own the overarching architecture of our cloud-native platform. You’ll work closely with engineering, product, and data science teams to ensure our solutions are scalable, performant, and strategically aligned. While product teams are responsible for their own component-level designs, you’ll play a critical role in ensuring those designs adhere to and evolve with our architecture.

Responsibilities:

• Own the Architecture: Define and evolve the system-wide architecture to support scalability, performance, and long-term growth of our SaaS platform.
• Partner on Design: Collaborate with engineering and data teams — who own their own designs — to ensure alignment with architectural direction and cross-team standards.
• Guide Technical Decisions: Participate in design reviews and provide clear guidance on architecture best practices, patterns, and trade-offs.
• Architect for ML at Scale: Establish architectural frameworks that support machine learning workflows, from data pipelines to model deployment and serving.
• Enable Agile Teams: Embed into agile squads to support design planning and technical decision-making early in the development cycle.
• Mentor and Align: Serve as a trusted advisor and mentor to tech leads and senior engineers, helping connect their local decisions to the company-wide technical strategy.
• Drive Tooling and Platform Choices: Evaluate and recommend infrastructure, platforms, and tools that enable scalability, resilience, and efficient development.

Requirements

You'll be a great fit if you have...

• 10+ years of experience in software architecture or system design for large-scale, cloud-based applications.
• Deep experience designing systems that incorporate big data and machine learning workflows in a SaaS environment.
• Strong architectural knowledge of cloud infrastructure — ideally Google Cloud Platform; AWS or Azure also welcome.
• Understanding of ML systems and pipelines, including data architecture, model training, and deployment strategies.
• Proven experience working within agile cross-functional teams, with the ability to drive architectural direction and technical outcomes without direct line management.
• Excellent communication and influencing skills, with the ability to balance technical vision with practical implementation.
• Passion for platform thinking, clean system design, and sustainable long-term architecture.

Nice to Have:

• Experience with MLOps tooling and processes.
• Exposure to event-driven architecture or service mesh patterns.
• Advanced degree in Computer Science or related field.
• Google Cloud Professional Architect or equivalent certification.