Lead Software Engineer - Network as a Product

The core of this role is combining platform engineering with deep networking expertise. We’re looking for someone who can build production Kubernetes control planes and translate complex network concepts into clean, declarative abstractions, enabling network engineers to express intent in YAML without needing to understand the underlying controller or device configuration.

You’ll bring an automation-first mindset and enough networking credibility to work effectively with senior engineers across routing, switching, and network infrastructure. You’ll understand where automation adds value, where it doesn’t, and help move the organisation away from accumulated manual changes toward consistent, infrastructure-as-code practices.

This is a technical leadership role, not a people-management role. You’ll help set platform direction, establish engineering standards, mentor engineers developing their software practices, and remain hands-on in building the platform. Whether you already lead a platform team or are a senior engineer ready for the next step, what matters is your ability to provide direction, create structure, and bring others along with you.

You’ll join CIE (Core Infrastructure Engineering) Physical Plane, the organization responsible for the global network connecting Nike’s distribution centers, retail stores, offices, and data centers. Physical Plane consists of five teams: three regional network engineering teams across NA, EU, and APLA, plus CIE Delivery and CIE Automation, which you’ll join.

CIE Automation owns the platform and automation layer for Nike’s global network. Based in EMEA, you’ll build the control plane used by regional teams to manage network changes, working alongside the Lead Engineer to provide technical leadership across platform strategy and control plane engineering.

You’ll partner closely with network engineers as they move from command-line operations to declarative infrastructure as code, while also collaborating across Cloud Core Engineering. The goal is to deliver the network as a product, using the same Managed Infrastructure principles as Cloud as a Product (CAAP), and establish an automation pattern that can scale across Nike’s global network estate.

• Own the Cisco control path. Build and extend the microservices that manage IOS-XE and NX-OS devices over NETCONF, including model handling, idempotency and failure behaviour that makes automation safe for production.
• Shape the intent model. Work with network engineers to define the YAML specifications they use to express what they want, finding the right balance between useful abstraction and the flexibility needed for real network requirements.
• Build the verification layer. Develop pre-change validation to confirm the network is in the expected state, and post-change verification to prove the change delivered the intended outcome without unintended impact.
• Make automated change auditable. Ensure the platform produces the evidence required for Change Control and CAB review, including diffs, pre- and post-change validation, rollback paths and blast radius.
• Make the developer experience good. Give engineers a fast, reliable way to develop, test and validate against the control plane locally, without needing to touch production.
• Migrate real networks onto the platform. Move production infrastructure onto the control plane one device class at a time, without disruption, and in a way that regional network teams trust and adopt.
• Bring SRE practice into the network. Define SLIs and SLOs, introduce RED and USE metrics, build operational dashboards, and use error budgets, toil reduction and blameless retrospectives to measure how well the platform is working.
• Extend into self-healing and closed-loop operations. Build towards drift detection, automated remediation of known failure patterns, and guardrails that prevent automated actions from making a bad situation worse.
• Coordinate delivery across teams. Work with regional network teams, Cloud Core Engineering and external partners to land changes end to end, set technical priorities and clear blockers.
• Use AI where it genuinely helps. Apply AI tooling to areas such as code generation and review, test scaffolding, documentation, operations and diagnostics, while being clear about where it adds value and where it doesn’t.
• Raise the engineering bar. Define standards for code reviews, testing, repository structure, documentation and release processes, and make the review expectations across SD-WAN, infrastructure as code, operational excellence and CaaP alignment concrete.
• Improve how the team works. Challenge processes that create friction or rely on manual knowledge, and establish better, more repeatable ways of delivering engineering work.
• Grow the engineers around you. Help strong network engineers who are earlier in their software journey become confident, independent contributors, both technically and professionally.
  

• Strong Go/Python and Kubernetes engineering experience: Production experience with Go, or strong Python experience with a genuine appetite to work in Go.
• Declarative control plane experience: Hands-on experience with Crossplane providers, compositions and composite resource definitions.
• Deep Cisco networking and automation expertise: Strong experience with NETCONF, YANG and RESTCONF across IOS-XE and NX-OS, combined with hands-on knowledge of Catalyst 9000 and Nexus platforms and their configuration, operational behaviour and failure modes.
• Strong network fundamentals: Deep understanding of routing and switching, including BGP, OSPF, VLANs and data center fabrics, with the ability to reason about the impact of changes on live production networks.
• API and data modelling experience: Experience designing schemas, APIs or intent models that other engineers consume, with sound judgement around abstraction, usability and long-term maintainability.
• GitOps, CI/CD and infrastructure testing: Practical experience designing declarative delivery pipelines, release processes and testing strategies for infrastructure code, using approaches such as controller test harnesses, virtual labs and staged environments.
• Microservices architecture: Experience designing service boundaries, contracts and versioning, including resilient behaviour when dependent services are unavailable.
• Technical leadership and influence: Ability to set technical direction and influence experienced engineers without formal authority, particularly when introducing new engineering or automation practices.
• Clear communication: Ability to explain complex technical platforms and their value to engineers, program managers, business stakeholders and senior leadership without losing the necessary technical nuance.
• Practical AI engineering mindset: Experience using AI tooling thoughtfully within engineering workflows, with a clear view of where it improves quality, speed or reliability and where it does not.
• Platform vision: Strong opinions on how modern network control planes and network automation should evolve, including the role AI can play, with the ability to turn that thinking into technical direction.

Applications will be accepted until 3rd November 2026. We encourage external candidates to apply as soon as possible, as the posting may close earlier if we receive a sufficient number of applications.