Own the architecture and hands-on development of an internal AI-assisted software development platform. Lead infrastructure, Kubernetes, Terraform-based environments, CI/CD, cloud security, observability, compliance automation, developer experience, and AI coding-tool sandboxing. Establish tenant isolation, identity, networking, governance gates, cost tracking, and reliability practices. Provide architecture leadership, mentor engineers and vendors, advise executives, and travel to clients as required.
The Opportunity
We’re partnering with a leading global management consulting firm that advises C-suite leaders on their most complex problems. The firm is building an internal platform to make AI-assisted software development consistent, secure, and repeatable across its product portfolio, covering everything from how code gets written and checked to how it ships and runs in production.
This role owns the foundation underneath all of it. You’ll set the technical direction for infrastructure, delivery, security, and developer experience, and you’ll build much of it yourself. The goal is a platform that every product team inherits by default and that keeps getting better after you’ve moved on to the next problem.
Expect a mix of hands-on engineering, architecture leadership, and mentoring. This role is remote within the U.S., but client travel is required. How much varies by client and time of year.
What You’ll Own
- Set the platform’s architecture: one container-orchestrated runtime, strong isolation between client engagements, and reusable, versioned infrastructure as code that spins environments up and down on demand
- Build identity, networking, and observability in from the start, with no long-lived credentials, just-in-time audited access, SLOs and alerting, and per-engagement cost tracking (AI spend included)
- Own shared CI/CD and the gate framework behind it, so quality, security, and AI-governance checks can block releases, and compliance evidence (scanning, signed artifacts, SBOMs, SOC2/ISO 27001) comes out of every build automatically
- Package the AI-assisted dev environment as a real product with hard sandbox boundaries for coding agents, and measure the platform by developer outcomes like setup time, pipeline speed, and adoption
- Lead major architecture decisions through written trade-off docs, advise senior stakeholders on platform risk, and mentor engineers and vendor partners
What You Bring
- 15+ years (Principal) or 10+ years (Staff) in software, platform, or infrastructure engineering. Platform work for consulting or professional services firms, including client isolation and data residency, preferred
- Fleet-scale infrastructure as code with Terraform or OpenTofu, plus Terragrunt or similar: module design, remote state, multi-environment layouts
- Production experience running multi-tenant Kubernetes, including GitOps, network and admission policies, workload identity, and tenant isolation. vcluster or Crossplane preferred
- CI/CD built as a shared platform (GitHub Actions or similar), with reusable workflows, org-wide branch protection, and enforced gates. Developer portal experience (Backstage, Port) preferred
- Hands-on cloud identity and network security on Azure, AWS, or GCP: workload identity federation, RBAC, private networking, WAF, DNS. Certifications such as Azure Solutions Architect, CKA/CKS, or CISSP preferred
- Security and compliance automation: scanners like Snyk, Checkov, or Trivy; policy engines like OPA, Kyverno, or Azure Policy; supply chain controls (signing, provenance, SBOM); SOC2 and ISO 27001 evidence. Experience sandboxing AI coding tools (Claude Code, Copilot, etc.) preferred
- Production observability with OpenTelemetry or similar: collector design, SLOs and error budgets, alert routing, incident response, chaos testing. FinOps experience (cost allocation, showback, optimization) preferred
- Real application development experience in Go, Python, or TypeScript, plus solid habits around testing, code review, trunk-based development, and releases
- Strong written and verbal communication, including with executives. A track record of teaching through internal docs, workshops, or engineering communities preferred
- Comfort working in Agile, cross-functional product teams
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