WHO YOU WILL WORK WITH:

This role reports into the Engineering Excellence and DevEx Organization and connects across all levels and functions of Global Technology at Nike to deliver engineering excellence solutions and platforms at scale. It is central to accelerating Nike's strategy to advance and evolve its technology landscape, delivering cost savings, better business agility, and faster time-to-market. The Director will partner closely with teams supporting foundational technologies across Nike's public cloud infrastructure, digital, retail, wholesale, and data centers globally.

WHO WE ARE LOOKING FOR:

This role leads the Engineering Excellence & Developer Experience organization — a team with a clear mandate: elevate how Nike engineers work, unify the developer tools ecosystem into a cohesive set of core platforms, and accelerate the adoption of AI-native development practices across Global Technology.
The Director will directly manage multiple engineering squads based in India, operating as part of a globally integrated team with counterparts in Beaverton, Oregon. This role partners with engineering leaders, product managers, and program managers enterprise-wide to define technical strategy, drive platform consolidation, and raise the engineering bar across Nike's global organization.

Key Qualification:

Education & Experience

Bachelor’s degree in computer science, Information Systems, or a related field, or any equivalent combination of professional experience, education, and training
At least 15+ years of overall technology leadership experience, including at least 5 years in a people management role building and leading effective, innovative teams through complex transformations — IC and management experience may overlap

Technical Leadership

At least 7 years developing highly available, highly scalable platforms using languages and technologies including but not limited to Java, Node.js, Golang, React, or JavaScript
At least 7 years of professional experience with Cloud Native technologies on platforms like AWS or other major cloud providers; proven experience addressing cloud challenges around clustering, end-to-end service design, resiliency, reliability, streaming, high availability / disaster recovery (HA/DR), and complex distributed systems
At least 4 years of professional experience with container runtimes such as Kubernetes, deployment tools like Terraform, and configuration management solutions like Ansible
At least 2 years leading AI-augmented engineering teams, implementing AI-native development practices, and driving developer productivity through AI tooling
Hands-on familiarity with agent-based development workflows and MCP (Model Context Protocol) ecosystems for enterprise software delivery

Developer Tools & Platform Experience

Deep foundational knowledge of software engineering practices, particularly distributed systems and cloud native architectures
Experience with developer tools ecosystem consolidation, including CI/CD platforms (GitHub Actions, Jenkins), artifact management (Artifactory, GitHub Packages), observability tools (Grafana, Databricks), and developer portals (Backstage)
Understanding of AI-native development workflows, agent-led software delivery, and human-supervised automation patterns including AI-assisted rapid prototyping methodologies

Leadership & Communication Skills

Excellent verbal and written communication skills, equally comfortable presenting to executives and working directly with engineering teams
High emotional intelligence with the ability to bring diverse groups together to tackle common goals while removing blockers decisively
Passionate about delivery, with the ability to provide technical direction while remaining a hands-on contributing member of the team
Long-term, holistic thinker who takes ownership of ambiguous problems and drives results with a strong emphasis on team productivity
Proven ability to engage and build trust with engineering communities, including navigating high-friction or resistant stakeholders, driving platform adoption through influence rather than mandate, and treating internal engineers as customers whose experience and feedback shape the work

Engineering Excellence Focus

Proven experience defining and implementing engineering productivity metrics, developer experience improvements, and measurable engineering outcomes that raise the technical bar across a global engineering organization

WHAT YOU’LL WORK ON:
You will lead engineering teams responsible for building and evolving Nike’s Engineering excellence and Dev Tooling strategy, engineering excellence, and developer Experience and drive adoption of AI-SDLC platform in india.

Your responsibility Includes:

Lead Engineering Excellence Transformation

Lead, mentor, and manage multiple engineering squads to deliver software that aligns to multi-year platform roadmaps, Global Technology standards, and modern industry trends
Drive the evolution of Nike's developer tools ecosystem into a cohesive set of core unified platforms: GitHub (CICD, Packages, Source Control), Nike AI SDLC Platform (AI Models, SDLC workflows, MCP Ecosystem, Governance), leverage Databricks (Metrics, Analytics, Automated Reporting), and build Backstage (Developer Portal, Docs, UI Plugins)

Strategic Engineering Excellence & Developer Tools

Lead multiple squads to evaluate, analyze, and advance Nike's technology landscape, engaging and partnering with the teams who build and maintain Nike's production systems and services
Define and lead the technical strategy, design, and engineering implementation of efficient, reusable, secure, and resilient technology solutions that modernize and evolve Nike's platforms in direct support of Nike's multi-year engineering excellence strategy

AI-Native SDLC Implementation

Drive Nike's technical maturity by establishing AI-native standards, best practices, and developer productivity improvements that set the benchmark for engineering culture across a global organization
Champion the adoption of AI-native SDLC practices where agents perform heavy lifting across the software delivery lifecycle while humans provide supervision at key checkpoints, moving from AI-assisted to agent-led development workflows

Cross-Team Collaboration & Communities of Practice

Foster cross-team collaboration across multiple engineering squads by growing and supporting communities of practice (COPs) for specialized multidisciplinary technical areas, including Observability, API, Data, AI/ML, Kubernetes, DevOps, Cloud, Pipeline, and Disaster Recovery
Lead coordination across geo-distributed teams and time zones to ensure consistent engineering practices and knowledge sharing across Nike's global technology organization
Establish and maintain traceability models connecting business requirements and outcomes to GitHub commits, deployments, and production signals for measurable engineering results