Manager, Software Engineering

Become a Part of the NIKE, Inc. Team

NIKE, Inc. does more than outfit the world's best athletes. It's a place where passionate individuals come together to create the future of sport. We are unapologetic about who we are and what we're after - bringing innovation and inspiration to every athlete* in the world. We look for athletes who can push boundaries, elevate our potential and continue leading us to greatness.

WHO YOU'LL WORK WITH

The Athlete Data Platform team builds the services, schemas, and data systems that give every Nike athlete a single, consent-aware record of who they are and what they're training for - and the intelligence layer that reads from it to power personalization across Nike Run Club (NRC), Nike Training Club (NTC), and the sport-science research surfaces behind them. As the Engineering Manager, you'll lead a full-stack squad spanning backend services, mobile SDK integration, and the data pipelines that keep the athlete record trustworthy end-to-end. You'll report to the Director of Engineering and partner daily with Principal and Lead Engineers, Sport Science, Data Science, Product, Design, the NRC and NTC app team, Privacy and InfoSec, and the Platform Engineering teams your services depend on.

WHO WE ARE LOOKING FOR

Nike is seeking an AI-Native Engineering Manager who leads full-stack delivery and can demonstrate - with concrete, recent examples - how state-of-the-art AI tools, agentic workflows, and spec-driven practices have accelerated the work of the teams they've led. You'll run the team that owns the per-athlete record and the intelligence layer that reads from it - a foundation other teams build on - and you'll be measured on how fast your team turns that foundation into shipped value. The ideal candidate has shipped platform services at consumer scale, has clear opinions on composable architecture and build-vs-buy, and can walk a hiring panel through the specific tools, loops, and metrics they use to compress weeks of work into days.

- Demonstrated fluency in AI-Native engineering - specific, recent examples of how state-of-the-art AI tooling and practices accelerated real delivery on teams you've led, with the architectural literacy to distinguish and apply the primitives: agents (the LLM decision loop) and multi-turn conversations (stateful, context-managed sessions); Model Context Protocol (MCP) integrations that expose Nike systems to those agents; workflow orchestration that chains agent steps deterministically; skills as composable guides (soft, loadable instruction packs) and hooks as deterministic gates (hard enforcement points in the dev loop); spec-driven development and evaluation harnesses that keep the whole thing honest - and clear-eyed judgment on what actually works vs. what just looks like it does
- 5+ years in technology and software engineering roles, including 3+ years in people management or team leadership; Bachelor's degree in Computer Science, Engineering, or a related field, or an equivalent combination of education, experience, and training
- Experience leading engineering teams in a highly matrixed environment, with the ability to drive outcomes across partner organizations you don't directly manage
- Track record leading full-stack squads shipping consumer-scale platforms - backend services, mobile SDK integration, and data pipelines - with ownership of availability, latency, and cost
- Hands-on technical grounding in modern backend stacks (Go, Kotlin/Java, or Python; ConnectRPC/gRPC/REST; event-driven pipelines on Kafka/Kinesis/SNS/SQS; cloud-native deployment on AWS or equivalent)
- Working familiarity with at least one mobile platform (iOS/Swift or Android/Kotlin) sufficient to lead technical reviews across backend ↔ client boundaries
- Experience partnering with Data Science, ML, or Sport Science teams to move models from notebook to production: data contracts, feature pipelines, evaluation, and safe rollout
- Working familiarity with the shape of activity and health data (GPS traces, sensor time series, HR/HRV, workout aggregates, training load) and the consent, privacy, and compliance expectations that come with them
- Strong track record hiring, growing, and performance-managing engineers across levels; comfort with difficult feedback conversations and succession planning
- Proven ability to lead technical design reviews, drive cross-squad alignment on service contracts and data models, and author written proposals that stakeholders at the Director and VP level can decide against
- Strong written and verbal communication across engineering, science, product, and executive audiences

WHAT YOU WILL WORK ON

You'll lead the engineering team behind the Athlete Data Platform - the record, the intelligence layer, and the pipelines that keep both trustworthy - and you'll be measured on how reliably that foundation unlocks the surfaces that depend on it. Your team's work is what makes the athlete-facing apps feel like they know the athlete: the plan that adapts actually adapts, the race recommendation is actually right, and the data NRC wrote is the data NTC reads.

- Build and operate the Athlete Data Platform team - hire, onboard, grow, and performance-manage a full-stack squad of senior and mid-level engineers plus a Lead or Principal IC partner
- Set the AI-Native engineering bar for the team - the agents, workflow orchestrations, MCP integrations, skills (as composable guides), hooks (as deterministic gates), spec-driven practices, and evaluation harnesses the squad uses day-to-day - and instrument how fast those practices actually move delivery, with the honesty to swap out what isn't working
- Partner with Principal Engineers, Product, Sport Science, and Data Science to set the quarterly roadmap and translate platform strategy into committed deliverables, with written specs reviewed before implementation starts
- Own the technical and operational health of the platform: service architecture, data-model quality, test coverage, latency, availability, cost, on-call load, and the consumer SLAs the NRC and NTC squads depend on
- Make and defend build-vs-buy calls for athlete data capabilities - where Nike's differentiation requires in-house platform ownership, and where a vendor integration is the right move
- Partner with the Activity Apps (NRC/NTC) iOS and Android squads on the SDK contracts, client-cache posture, and offline/online reconciliation behavior that keeps the athlete record consistent across apps and devices
- Partner with Sport Science and Data Science to productionize models grounded in Nike Sport Research Lab (NSRL) biomechanics, fueling, and recovery research - data contracts, feature pipelines, evaluation harnesses, consent-aware inference, and safe progressive rollout
- Partner with Security, Privacy, and Data Governance to keep athlete data - location, health, biometric - safe, consent-aware, and compliant end-to-end
- Represent Athlete Data Platform in cross-MAC architecture reviews, platform-readiness sequencing, and executive forums; translate between engineering, science, and business audiences
- Grow the technical bar on the team through structured feedback, design-review coaching, and mentorship across levels

WHAT YOU BRING

- A bias to action balanced with the discipline to write a spec before writing code
- Deep pride in craft, and a habit of leaving teams and systems stronger than you found them
- A team-first orientation - you scale yourself by making the engineers around you better and the systems around you simpler
- Curiosity about the athlete and the science behind the data your team moves
- Clear-eyed judgment on AI tooling - excitement about the leverage, honesty about what actually works

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form .