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разработка

Platform Engineer

Yael Acceptic14 дн. назад

Коротко

Builds and operates internal platform: GitOps, Kubernetes, Terraform/OpenTofu, AWS (EKS, IAM, S3, RDS, Lambda, CloudWatch); uses AI coding assistants and · Needs: Platform engineering experience; AWS and networking proficiency (VPC, subnets, CIDR, route tables, security groups, NACLs, peering, Transit Gateway).

Описание от работодателя

We are looking for a Platform Engineer to join the team — a persone who collaborates, innovates, and treats every problem as a mission to be completed. You will help build and operate the internal platform that other engineering teams depend on: GitOps delivery, Kubernetes-based runtime, infrastructure automation, and developer self-service capabilities. You will use AI and Agentic AI as everyday tools to accelerate everything you do — code generation, automation, troubleshooting, documentation, and platform tooling. About: Our client is developing electro-mechanical devices for dairy farms, pulsators and automatic detachers. The solution is leading in the industry with advanced cow monitoring solutions based on activity and rumination sensors. Responsibilities: Platform Engineering (Core): Build and operate the internal platform: GitOps delivery, Kubernetes runtime, infrastructure automation, and developer self-service capabilities; Apply platform-as-product thinking — product teams are your customers; developer experience is the metric; Contribute to the team's evolution toward IDP capabilities on Port, Crossplane, and self-service control planes; Maintain and extend Infrastructure as Code (Terraform / OpenTofu) for platform components; Ship POCs that turn into platform capabilities. AI & Agentic AI in Daily Work: Use AI coding assistants (Claude, Copilot, or similar) for code, IaC, and platform automation; Design and use agentic AI workflows to automate repetitive platform tasks — investigation, remediation, documentation, scaffolding; Build AI-augmented tooling into the platform itself where it accelerates product teams; Set the bar for the team on responsible, effective use of AI in engineering work. Cloud, AWS & Networking (Foundational): Operate confidently in AWS: EKS, IAM, S3, RDS, Lambda, CloudWatch; Networking proficiency is required: VPC design, subnets, CIDR planning, route tables, security groups, NACLs, peering, Transit Gateway, VPC endpoints, DNS (Route53); Troubleshoot connectivity, ingress/egress, and cross-account/cross-VPC traffic flows; Apply networking knowledge to Kubernetes: Services, Ingress, Network Policies, CNI behavior. GitOps & Kubernetes (Day-One Operational): Operate ArgoCD as a core platform capability: GitOps workflows, application/infrastructure delivery, multi-environment promotion; Own ApplicationSets-driven multi-version, branch, and PR deployment patterns — providing the platform capability while product teams consume it; Deploy, troubleshoot, and instrument Kubernetes workloads; Apply progressive delivery patterns (canary, blue-green) where they fit. GitHub Org & Artifact Management (Platform-Owned): Manage the GitHub organization as a platform service: orgs, teams, repos, templates, code owners, branch and environment protections, secrets, OIDC to AWS; Build and maintain reusable GitHub Actions workflows that product teams consume out of the box; Operate CI bots for PR validation, auto-labeling, auto-merge on green, and policy enforcement; Curate Copilot org policies and custom Copilot instructions so AI assistance is consistent and safe across repos; Operate JFrog Artifactory as the artifact backbone: registries, retention, promotion paths, Xray scanning, and signed artifacts flowing through environments. Collaboration & Leadership: Collaborate with CloudOps, DevSecOps, FinOps, and SRE — peer-to-peer, not siloed; Mentor team members; deliver POCs, technical presentations, and documentation; Bring innovation to the team: new tools, new patterns, new ways of working; Champion shared standards across the platform community. Requirements: 7+ years in Platform Engineering, SRE, or closely related roles; Platform mindset — you build platforms and self-service capabilities; you do not run a ticket queue; AI fluency: hands-on daily use of AI coding assistants and agentic AI workflows to deliver engineering work; AWS proficiency: EKS, IAM, S3, RDS, Lambda, CloudWatch, and the operational fundamentals; AWS networking: VPC, subnets, CIDR planning, route tables, security groups, NACLs, peering / Transit Gateway, VPC endpoints, Route53 — confident designing and troubleshooting multi-VPC topologies; Kubernetes: strong operational proficiency — deploying, troubleshooting, and instrumenting workloads (not cluster architecture); ArgoCD & GitOps: multi-environment Kubernetes deployments, ApplicationSets, progressive delivery; Terraform / OpenTofu: proficiency with declarative infrastructure management; CI/CD: tool-agnostic pipeline design (Azure DevOps, GitHub Actions, or both); GitHub as a platform: org/team/repo administration, reusable Actions workflows, branch and environment protections, OIDC to AWS, CI bots for PR validation and auto-merge, and Copilot org policies / custom Copilot instructions; Artifact management: hands-on with JFrog Artifactory (or directly comparable, e.g., Nexus, GitHub Packages at scale) — registries, retention, promotion, vulnerability scanning; Scripting: Python, Go, Bash, or similar for automation and tooling; Team player and assertive collaborator: works effectively across Platform, CloudOps, DevSecOps, FinOps, and SRE functions; takes initiative and finishes missions; IDP tools (Stack Port, Backstage) — central to where the team is heading; Crossplane for Kubernetes-based infrastructure management; Argo ecosystem depth (Rollouts, Workflows, Events); SRE practices: SLOs, SLIs, error budgets, incident response, post-incident reviews; DORA metrics: defining, tracking, and driving measurable delivery improvement; Building or operating internal AI-powered developer tools; At least Upper-Intermediate English level. Would be a plus: Observability: Datadog, OpenTelemetry, Prometheus & Grafana — instrumentation, dashboards, alerting (a Plus, not a requirement); Service mesh (Istio, Linkerd); FinOps practices and cloud cost optimization tooling; Policy as Code (OPA, Kyverno); Certifications: CKA/CKAD, AWS Solutions Architect/DevOps Engineer/Advanced Networking, HashiCorp Terraform. We offer: Growth: Udemy corporate access, corporate English program, and educational meetups from partners. Health: Medical insurance, psychological support, and fitness discounts. Comfort: 100% paid vacation days and sick leaves and power-independent offices (Generators/Starlink). Beyond Work: Free legal advice, referral bonuses, and loyalty program.