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Fetcherr is an AI company building responsible, market-intelligence technology that delivers demand predictions and real-time decision intelligence for commercial teams. The company's proprietary Market Model uses market data with full transparency and has achieved 96% forecast accuracy, driving an average 7% profit uplift for customers including Delta, Virgin Atlantic, WestJet, and Azul.
As DevOps Team Lead, you will lead the platform engineering transformation as Fetcherr scales across new verticals and markets. You'll own the evolution from a carefully operated platform to a Kubernetes-native, self-service product that empowers internal engineering teams.
Key responsibilities include:
**Self-Service Enablement**: Design and implement secure, automated infrastructure pathways that accelerate development velocity while maintaining organizational standards and safety.
**Architectural Modularization**: Transform infrastructure into a decoupled, scalable architecture supporting rapid iteration and independent service lifecycles. Implement "Everything as Code" practices for infrastructure, policy, and configuration.
**Unified Infrastructure Management**: Establish rigorous operational standards, treating infrastructure with the same discipline as application software.
**Proactive Reliability**: Foster operational excellence through robust observability, clear Service Level Objectives, and a culture of safety-first engineering.
**Team Leadership**: Build and grow a high-performing platform engineering team. Empower engineers with context and autonomy, foster learning through blameless postmortems and retrospectives, and eliminate single points of failure.
Success metrics include 30% reduction in deployment lead times and 50% increase in self-service adoption within 6 months, with 99.9% uptime for core services. By 12 months, establish the Platform Engineering team as an autonomous, high-scale unit setting the standard for engineering excellence.
You are a hands-on leader who delivers sustainable value, empowers rather than directs, and maintains technical credibility. You prioritize "the how"—tested, reviewed, observable, highly available solutions—and define done as production-ready, customer-serving code.
