Professional Services Deployment Engineer

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🕒 3 dias atrás

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

⛑ DevOps & Engenheiro de Confiabilidade do Site (SRE)

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ArangoDB

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2015

🏥 Saúde

📦 Logística

💼 Consultoria

💰 $27.800.000 Series B em 2021-10

Healthcare • Logistics • Consulting

ArangoDB é uma plataforma moderna de banco de dados de grafos que oferece uma solução abrangente para aplicações de Graph ML e GenAI. Conhecida por sua flexibilidade e escalabilidade, a ArangoDB integra, em uma única plataforma, sistemas de dados de grafos, documentos, busca full-text, chave-valor e geoespaciais. Isso permite que os usuários abordem diversos casos de uso, como detecção de fraude, cibersegurança e gestão de ativos de rede, com facilidade. A plataforma suporta uma ampla variedade de ambientes de implantação, incluindo cloud e Kubernetes, e oferece recursos avançados como análise de grafos, machine learning e ferramentas de visualização. Com sua robusta linguagem de consultas AQL e foco em inovação, a ArangoDB se destaca como líder em tecnologia de bancos de dados de grafos.

Descrição

• Deploy ArangoDB and ArangoAI components across AKS, EKS, OpenShift, and on-prem clusters • Build and maintain Helm-based deployment bundles, including combined stacks • Troubleshoot Kubernetes-level issues including PVC/PV mapping, storage performance, pod scheduling, cluster access, and network policies • Diagnose and resolve load balancer issues, connection timeouts, and service routing problems • Validate cluster health, storage provisioning, and performance baselines • Train customer teams to become self-sufficient in cluster operations, monitoring, and upgrades • Create documentation, training, and deployment guides • Lead hands-on workshops and labs • Provide one-time setup support while coaching teams toward long-term ownership • Investigate performance issues across compute, storage, and query layers • Review query plans, vector index usage, and full-scan patterns with DBAs and ML engineers • Help customers navigate platform constraints such as lost SSH access, misconfigured jump boxes, and degraded cluster states • Collaborate with internal engineering to surface recurring issues and improve deployment automation • Partner with platform teams to align deployment patterns • Work with product engineering to validate new features in real-world environments • Coordinate with customer project leads to ensure smooth onboarding and predictable delivery

🎯 Requisitos

• 4+ years of deployment engineering experience • Strong experience with Kubernetes, including AKS, EKS, and OpenShift • Experience with Helm • Solid understanding of AWS and Azure cloud infrastructure • Experience with on-prem environments • Familiarity with EBS, gp3, MinIO, and S3-compatible storage • Ability to debug load balancers, timeouts, service endpoints, DNS, and ingress controllers • Experience with distributed systems or databases such as ArangoDB or Neo4j • Comfort with Linux, SSH, jump boxes, and cluster-admin workflows • Clear, calm communication and ability to translate complex systems into simple explanations • Patient training approach and ability to build team confidence • Strong ownership and ability to work in fast-moving environments with shifting priorities

🏖️ Benefícios

• Contributing to cutting-edge AI and data infrastructure • Collaborating with experienced engineers, marketers, and product leaders • Helping shape how enterprises build AI-powered applications • Diverse and inclusive team • Support for employees and interns as they learn, grow, and contribute