Engineer II, Platform

NIGHTINGALE EDUCATION LLC SOLE MB•Salt Lake City, UT

2d•Onsite

About The Position

Platform Engineering exists to multiply the productivity of the entire technology organization and the enterprise. We don't chase tickets or patch one-off problems for individual teams — we identify the recurring friction, the systemic gaps, and the shared infrastructure needs that slow everyone down, and we build durable solutions that solve such issues once and for all. We treat the internal platform as a product. Our customers are those who build on it — and also the technical power users across the organization who operate our other platforms day to day. Success means all of them ship and operate faster, more safely, and with less cognitive overhead because the paved paths, tooling, and infrastructure we own will simply work. The team also owns enterprise architecture: keeping our major systems well integrated and coherent, and partnering on the system design and architecture for new systems, services, and applications before they're built. We're as responsible for how the whole landscape fits together as we are for the platform underneath it. As the organization grows into a scalable enterprise, we lead the move toward a “bigger, better, fewer” philosophy — consolidating onto fewer, stronger (scalable) systems and dependencies to raise our operational maturity rather than accumulating sprawl. We're looking for a Platform Engineer who thinks at the system level, is comfortable across a multi-cloud environment, and is as strong with people and communication as they are with code and infrastructure.

Requirements

Multi-cloud systems and networking. Hands-on experience operating production workloads across more than one cloud (GCP and AWS preferred), including cross-cloud and site-to-site networking and the tradeoffs between providers.
Terraform. Strong infrastructure-as-code discipline — modular, reviewable, and built for a team to maintain rather than one person to understand.
Kubernetes. Deep practical knowledge of cluster operations, networking, and workload management, plus the judgment to know when not to add complexity.
Go and Python. Able to build and maintain real services and tooling, not just scripts.
Web applications and data pipelines. Familiarity — required at every level — with how modern web applications and data-engineering pipelines are built, deployed, and operated.
Cybersecurity. A security-first mindset applied to access control, identity, secrets, and infrastructure hardening.
RBAC and access management. Strong working knowledge of role-based access control and identity platforms (e.g., Entra ID), including standardized role modeling.
AI tooling. Familiarity integrating LLMs such as Claude into developer workflows and internal applications.
System design, architecture, and integration. Comfortable designing systems at the org level and reasoning about how major systems integrate into a coherent enterprise architecture.
Communication. Can explain technical tradeoffs clearly to both technical and non-technical stakeholders, write crisp design docs, and build alignment across teams.
Leadership. Sets technical direction, influences without authority, mentors other technologists, and drives platform decisions to resolution rather than letting ownership stay ambiguous.
Service mindset. Genuinely treats all collaborators as customers. We borrow three pillars from great service: gain agreement — make sure you actually understand the problem before solving it; empathy — everyone deserves it, every time; and ownership — take the problem on and see it through to resolution rather than handing it off. Prioritizes by impact across the org.
Pragmatism. Biases toward operationally simple solutions and is willing to have their own designs stress-tested rather than defended.
Relationships. Builds and sustains solid, trust-based relationships with leaders across the company — technical and non-technical alike.
Business and shareholder value. Understands that everything we do and build should add stakeholder value.
Growth mindset. On this team the learning is never done. We want people who are more curious than certain — who treat being wrong as information, keep learning as the landscape shifts, and grow as fast as the organization does.
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.

Nice To Haves

Familiarity with SASE platforms such as Cato — including administering the network and establishing site-to-site connections to vendors — is a strong plus.
Experience building developer platforms or internal developer portals.
Background in SRE or DevOps and familiarity with SLA/SLO frameworks.
Exposure to data platforms and enterprise system integration.

Responsibilities

Identify problems common to multiple technology teams and design platform-level solutions instead of bespoke fixes.
Build and operate self-service infrastructure, tooling, and paved paths that let product teams move quickly without reinventing foundations.
Own CI/CD pipelines and the guardrails that ensure code deploying to production is high quality and secure.
Drive site reliability design and structure — defining and meeting reliability targets, reducing toil, and keeping production healthy and observable.
Own multi-cloud infrastructure (currently GCP and AWS) as code, including networking, compute, and the connective tissue between providers.
Administer the Cato (SASE) network and handle a good amount of hands-on networking — including standing up new site-to-site connections between Cato and our major vendors.
Design and maintain Kubernetes-based platforms — cluster architecture, workload patterns, and the developer-facing abstractions on top.
Write production-grade internal tooling and services in such technologies as Go and Python.
Embed security into the platform by default: least-privilege access models, RBAC, secrets management, and secure-by-default infrastructure patterns. As owners for AWS, GCP, and GitHub, help govern how access is granted and governed for teams and individuals.
Integrate AI capabilities (e.g., Claude) into internal developer tooling and workflows where they meaningfully reduce toil.
Lead system design and architecture decisions, weighing tradeoffs, and documenting the decisions clearly for stakeholders.
Own enterprise architecture: maintain a coherent view of how major systems fit together and drive the integration work that keeps them connected and consistent.
Partner on the design and architecture of new systems, services, and applications early — shaping them before they're built rather than reacting after.
Build automations and streamline workflows for peer functions such as ITSM and IT Demand Management, reducing manual effort and improving how work flows across the organization.
Drive system and dependency consolidation under a “bigger, better, fewer” approach, retiring redundant tools in favor of fewer, more capable platforms as the organization matures.
Partner with technology teams and technical power users to understand their pain, prioritize platform investments by leverage, and measure the impact of what you ship.
Help with special projects such as AI tutors and other applied-AI initiatives, and actively look for ways to leverage AI to advance the future of education and of our operations.
Prototype new possibilities and leverage AI to advance the future of education and operations.