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Phizenix

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Phizenix

Staff Platform Engineer

Phizenix · Remote · posted 18 days ago
ApplyFull posting

Extracted from the posting

Base
Not stated
Remote
Remote
Stack
Kubernetes, Docker, Terraform

The posting, condensed

Staff Platform Engineer designing container-orchestrated runtime, infrastructure-as-code templates, and shared delivery pipelines with security/compliance gates. Requires 10+ years in platform/infrastructure engineering with hands-on Terraform/OpenTofu, multi-tenant Kubernetes, GitHub Actions, and cloud identity/network security expertise.

About Phizenix →

The full posting

This is a hands-on engineering position where leadership happens through the work. You will move fluidly between building production infrastructure, implementing multi-tenant isolation, hardening pipeline and policy enforcement, and instrumenting production. Your success is measured by what other engineers can consume without hand-holding: modules, pipelines, and patterns that hold up for the second and third consumer.

What You'll Do

Platform Infrastructure Engineering

  • Build the platform's runtime: implement one container-orchestrated runtime, tenancy-grade isolation between client engagements, and the module contracts every product inherits.
  • Design composable infrastructure as code at fleet scale, with clear input contracts and state boundaries, published as versioned templates and images for every core component.
  • Make the environment lifecycle a one-command operation: created by merging a pull request, destroyed by deleting it, with automated proof nothing is left behind.
  • Design identity and network as a federated, credential-free system — one identity per engagement, just-in-time audited privileged access, separate internal and external edges.
  • Ship telemetry and cost visibility out of the box for every service: standard alerting, service-level objectives on live data, fault injection, and per-engagement cost attribution including AI spend.

Delivery Pipelines, Security & Compliance Engineering

  • Build and operate the shared delivery pipelines every product runs through, and the pluggable gate framework that quality, security, and AI-governance checks plug into with block-on-fail enforcement.
  • Implement security and compliance as code: release-blocking scanning on every repository, policy and admission control, signed and attested artifacts, and an audit trail and software bill of materials, including AI components, on every build as SOC2 / ISO 27001 evidence.
  • Package the AI-assisted development environment as a versioned, first-class deliverable, and enforce the sandbox boundary for coding agents: default-deny egress, short-lived credentials, isolated shared runners.
  • Run the platform as a product measured by developer outcomes — setup time, time to first commit, pipeline duration, gate false-positive rate, adoption — pruning or redesigning controls when governance burden outgrows benefit, and proving every golden path by shipping through it yourself.

Technical Leadership & Engineering Excellence

  • Make the platform's architecture decisions decidable — multi-tenancy, cloud posture, identity provider, network edge — by building the spikes and proofs of concept behind them, and produce the security and reliability evidence the program reports against.
  • Be the engineer other engineers come to on infrastructure, pipelines, and enforcement:review designs and pull requests, write architecture decision records for anything that closes off future options, and raise the bar for vendor partners through the work rather than formal management.
  • Drive adoption of platform standards across product teams, supporting migrations onto the platform where product teams execute and you unblock.

What You'll Need

Required

  • 10+ years in software engineering, platform or infrastructure engineering, or a closely related technical field.
  • Hands-on expertise in infrastructure as code at fleet scale (Terraform or OpenTofu with Terragrunt or equivalent): module architecture, remote state, multi-environment topology.
  • Demonstrated experience operating multi-tenant Kubernetes platforms in production: GitOps, network and admission policy, workload identity, tenant isolation.
  • Experience building CI/CD as a shared platform (GitHub Actions or equivalent), with reusable workflow contracts, fleet-scale branch protection, and enforced quality and security gates.
  • Strong hands-on command of cloud identity and network security on Azure/AWS/GCP or a comparable hyperscaler: workload identity federation, RBAC, private networking, WAF, DNS.
  • Substantive experience with security and compliance as code: scanning toolchains (Snyk, Checkov, Trivy), policy engines (OPA, Kyverno, Azure Policy), supply chain controls (signing, provenance, SBOM), and SOC2 / ISO 27001 control evidence.
  • Production observability with OpenTelemetry or equivalent: collector topology, SLOs and error budgets, alert routing, incident management, fault injection.
  • Has built and operated production application software as a software engineer, in at least one of Go, Python, or TypeScript, and is fluent in testing strategy, code review, trunk-based delivery, and release management.
  • Excellent written and verbal communication skills in English; ability to translate complex technical topics to diverse audiences, including engineering and non-technical stakeholders.
  • Experience with Agile methodologies and cross-functional product team collaboration.

Preferred / Additional Qualifications

  • Experience building platforms for consulting, advisory, or professional services, including client-isolation and data-residency requirements.
  • Familiarity with virtual-cluster and control-plane tooling (vcluster, Crossplane) and developer portals (Backstage, Port).
  • Experience operating a platform used by AI coding assistants (Claude Code, GitHub Copilot or similar), including sandboxing of agent tooling.
  • Advanced certifications in cloud architecture, Kubernetes, or security (e.g., Azure Solutions Architect, CKA/CKS, CISSP).
  • FinOps experience: cost allocation, showback, and cloud cost optimization.
  • Demonstrated enthusiasm for developer education — writing internal guides, running workshops, or building internal tooling communities.