DevOps Engineer

Tomorrow.io's Engineering department is focused on building life-changing software and products at scale, from infrastructure that handles massive amounts of data to outstanding customer-centric user experiences in B2B, B2C and B2D products that change billions of lives worldwide.

We're looking for a DevOps Engineer to power the reliability, security, and efficiency of the world's most impactful weather platform. You'll build self-service platforms that give developers and weather scientists true independence, weave AI into how we operate, and work side-by-side with R&D to push performance and scale further. You'll evolve our cloud infrastructure to match the pace of the business, hold the line on cost, and stay close to production through on-call. The people who thrive here bring a product mindset, take ownership without waiting to be asked, and leave the people and systems around them better than they found them.

As a DevOps Engineer at Tomorrow.io, you'll:

Evolve and maintain our cloud infrastructure, delivery and observability - and the self-service platforms above them - so they serve our business strategy and let scientists and developers work on their own as we grow at scale__Develop and adopt tools, with AI at the center, that make development and operations processes measurably more efficient__Partner with the engineering teams behind the Tomorrow.io platform and its API to improve service performance, reliability, scale, security and cost__Keep production available to its SLOs - taking your turn on the on-call rotation and following each incident through to whatever stops it from happening again__Work as part of the team: share what you know, learn from the people around you, and help us keep improving how we work together

What you bring:

• 4+ years as a DevOps / Platform Engineer, including 2+ years hands-on with a major cloud (GCP, AWS or Azure) and with IaC such as Terraform (Crossplane or another Kubernetes-native approach is a plus)
• Production Kubernetes depth - containerized deployments, scheduling, resource management and real troubleshooting - plus CI/CD pipelines you've built and owned end to end with modern tooling and advanced deployment methodologies
• Experience implementing and customizing monitoring and observability systems (Datadog, Grafana + Loki, Prometheus, ELK)
• Software engineering craft and the judgment to review, debug and improve what an agent produces
• Hands-on use of AI tooling in your engineering work - shaping and extending it (agents, rules, integrations), not only consuming it