
51 - 200 Mitarbeiter
Gegründet 2021
🤖 Künstliche Intelligenz
🤝 B2B
🏢 Unternehmen
Artificial Intelligence • B2B • Enterprise
Shuru ist ein Beratungsunternehmen für Produkte, KI und Technologie, das mit Unternehmen zusammenarbeitet, um strategische Beratung, vollständige Produkt- und individuelle Softwareentwicklung sowie maßgeschneiderte Engineering-Teams zu bieten. Ihre KI-nativen Engineering-Teams entwickeln skalierbare KI-Anwendungen, Datenengineering und -analysen, Cloud/DevOps und API-Integrationen, um Systeme zu modernisieren und die Produktlieferung zu beschleunigen. Shuru operiert global mit einem Remote-First-Modell und legt Wert auf hohe Verantwortung, Design Thinking und messbare Ergebnisse für Unternehmenskunden und Start-ups.
🕒 vor 4 Monaten
🗣️🇺🇸🇬🇧 Englisch erforderlich
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51 - 200 Mitarbeiter
Gegründet 2021
🤖 Künstliche Intelligenz
🤝 B2B
🏢 Unternehmen
Artificial Intelligence • B2B • Enterprise
Shuru ist ein Beratungsunternehmen für Produkte, KI und Technologie, das mit Unternehmen zusammenarbeitet, um strategische Beratung, vollständige Produkt- und individuelle Softwareentwicklung sowie maßgeschneiderte Engineering-Teams zu bieten. Ihre KI-nativen Engineering-Teams entwickeln skalierbare KI-Anwendungen, Datenengineering und -analysen, Cloud/DevOps und API-Integrationen, um Systeme zu modernisieren und die Produktlieferung zu beschleunigen. Shuru operiert global mit einem Remote-First-Modell und legt Wert auf hohe Verantwortung, Design Thinking und messbare Ergebnisse für Unternehmenskunden und Start-ups.
• Kubernetes platform engineering (EKS-first) ● Design, build, and operate production-grade Kubernetes clusters (multi-nodegroup, autoscaling, upgrades, cluster add-ons). • Implement intelligent autoscaling using real metrics (queue depth, consumer lag, service latency) via tools like KEDA/Karpenter. • Own AWS environments end-to-end (VPC, IAM, EKS/ECS/EC2, ALB/ELB, S3, Route53, CloudWatch, RDS, SQS, Lambda). • Build reproducible infrastructure using Terraform, with strong review + change management practices. • Implement backup/DR patterns (e.g., snapshots, retention, automation) and safe rollouts. • Design infrastructure for data-intensive workloads: high-throughput ingestion, batch processing, and real-time streaming. • Understand and operate distributed systems at scale — consensus, partitioning, replication, and failure modes. • Build and maintain infrastructure for data pipelines, vector databases. • Design for horizontal scalability, ensuring systems handle growing data volumes and user traffic gracefully. • Build/own monitoring + logging from scratch and make it actionable (Prometheus/Grafana, ELK/EFK, alerting). • Define/partner on SLI/SLOs and incident response practices; improve reliability with data-driven changes. • Establish performance testing and production-like load testing environments. • Continuously reduce AWS spend via right-sizing, Spot strategies, reserved capacity planning, and architecture improvements. • Partner with engineering teams to diagnose bottlenecks (db queries, caching, queueing) and propose scalable solutions. • Optimize infrastructure costs for data-heavy workloads (storage tiering, compute scheduling, GPU utilization). • Improve cloud and cluster security posture (IAM, network policies, secrets management, least privilege). • Support SOC2 readiness/execution (controls, evidence automation, operational hardening). • Implement access management patterns.
• 7+ years in DevOps / SRE / Cloud Infra roles operating production systems. • Deep hands-on experience with Kubernetes in production. • Strong AWS fundamentals across compute/networking/storage/identity, including VPC, IAM, EC2/EKS, ALB, S3, Route53, CloudWatch, RDS, SQS. • Proven ability to build infra using Terraform (and strong IaC practices). • Production-grade observability experience: Prometheus + Grafana, and centralized logging (ELK/EFK or similar). • Experience scaling product infrastructure — you've grown systems from thousands to millions of requests, and understand capacity planning, bottleneck identification, and scaling patterns. • Solid understanding of distributed systems concepts: CAP theorem, consistency models, partitioning strategies, distributed consensus, and failure handling. • Strong understanding of databases and performance fundamentals. • CI/CD experience building reliable pipelines (Jenkins/Spinnaker/GitHub Actions equivalents), with safe deployment strategies. • Scripting/automation ability in Python and/or Bash (Go is a plus).
• Competitive salary and benefits package. • Opportunity to work with a team of experienced product and tech leaders. • A flexible work environment with remote working options. • Continuous learning and development opportunities. • Chance to make a significant impact on diverse and innovative projects.
Jetzt Bewerben🕒 vor 4 Monaten
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