Principal Platform Engineer - Hybrid​/Remote

Our client is a top-tier strategy and management consulting firm, the kind that competes with McKinsey, BCG and Bain for C-suite work. They are building an AI-native development platform that standardizes how code is generated, verified, secured, deployed, and monitored, so AI-assisted product development is safe and repeatable across its portfolio.

The Principal Platform Engineer sits at the intersection of infrastructure, delivery engineering, security, and developer experience. You will be accountable for the substrate every product - infrastructure as code, delivery pipelines and their gates, the runtime, identity and network, security and compliance controls, telemetry and cost, and the packaged development environment that carries our AI-assisted engineering harness.

This is a hands-on engineering and technical leadership position. You will move fluidly between building production infrastructure, architecting multi-tenant isolation, designing pipeline and policy enforcement, leading strategic architecture decisions, and mentoring engineers. Your success is measured by what every product inherits: a compounding system that outlasts your direct involvement. Travel is part of this position, but frequency may vary based on client, team, and individual circumstances.

• Drive the platform's architecture and runtime direction, including convergence onto one container-orchestrated runtime, tenancy-grade isolation between client engagements, and the 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.

• Drive 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.

• Lead the platform's strategic architecture decisions — multi-tenancy, cloud posture, identity provider, network edge — as evidence-based decision documents with real trade-offs, and own the security and reliability evidence the program reports against.
• Serve as a go-to technical authority on platform architecture and delivery engineering, consulted by senior stakeholders at the design and strategy stages,…