Senior DevOps Engineer

Description

Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul.

Fetcherr is scaling rapidly, and we are transforming our internal infrastructure into a high-velocity, self-service product. This is a senior opportunity to architect the future of our platform, setting the technical standard for how we deliver services while ensuring reliability and developer independence across diverse global markets.

Responsabilities:

• Self-service enablement: Build secure, automated pathways that accelerate development while keeping organizational standards intact.
• Architectural modularization: Design Kubernetes-native abstractions — controllers and operators — and decouple infrastructure into independent service lifecycles that support rapid iteration.
• Everything as code: Treat infrastructure, policy, and configuration with the same SDLC as application software — versioned, reviewed, tested, and CI-gated.
• Proactive reliability: Own production through robust observability, clear SLOs, and high operational hygiene; define alerting that fires correctly and lead blameless postmortems that fix the system.

Requirements

• Strong GCP experience at production scale (GKE, IAM, networking, Cloud SQL/BigQuery). No compromise here.
• Kubernetes-native mindset: declarative-first, comfortable with controllers and operators, and a platform-engineering instinct for self-service and separation of concerns.
• Everything-as-code discipline: any code ships through a defined SDLC (versioned, reviewed, tested, CI-gated). Terraform (KCC a plus), Helm, GitOps (ArgoCD or similar) in your toolkit.
• Software engineering background, or proven strong development ability in Go and/or Python — you write production code, not just glue scripts.
• Security awareness baked into how you build: least-privilege IAM, secret hygiene, policy and supply-chain gates, not bolted on after.
• Production-first mindset: you design for reliability, observability, and recoverability, and you own what you ship.

Nice to have:

• Policy-as-code (OPA/Conftest, Kyverno) and supply-chain/CI security tooling.
• SLO/error-budget practice and DORA-based delivery measurement.
• Multicloud experience (AWS / Azure) — GCP is home, but breadth helps.
• Big Data or MLOps exposure (Airflow, Dagster, Ray, Kubeflow).
• A point of view on AI-assisted and spec-driven development.