Phizenix - Staff Platform Engineer
Requirements
• 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. • 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.
Responsibilities
• 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.
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