Engineering Director, AI Developer Experience (AIDE)

ABOUT NU Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services. Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability. Visit our Institutional Page https://www.nu.com/2026-en About the team This role sits within Global Platforms Engineering: Engineering Enablement, under Eric Young https://www.linkedin.com/in/ericcyoung/ (CTO, Global Platforms Engineering). The AI Developer Experience (AIDE) pillar is the AI-native counterpart to the separately led Developer Infrastructure pillar: a standing topic in CTO org-design reviews. Reports to a Senior Director, Engineering Enablement and dotted line to Rahul Ahlawat https://www.linkedin.com/in/rahul-ahlawat, Engineering Senior Director & Chief of Staff to the CTO. Leads a team of approximately 10–15 engineers today, spanning five workstreams, scaling with 8 committed "Deep Forge" headcounts plus external hiring. This is green-field scope with established backing: the charter, budget conversations, and headcount pipeline already exist. The Director shapes execution and strategy, not just strategy alone, and has real decision-making authority over team structure, build-vs-buy calls, and workstream prioritization. The Director will also engage directly with third-party AI vendors (e.g., Factory.ai, Devin-class tools) and with ICs across the five core workstreams. About the role Nu is one of the few companies with the scale (3,500+ engineers), AI ambition, and executive air cover to build a genuinely AI-native developer experience: not a bolt-on pilot. This role is responsible for defining and leading the AI Developer Experience pillar within Engineering Enablement, transforming how Nu's engineers write, review, deploy, and operate software. The Director inherits a mandate, a growing team, and a seat at the table with the CTO. The pillar already has real momentum: an early production win in the Vector agentic coding platform, an urgent context-infrastructure buildout, and direct executive sponsorship. Key responsibilities and Expectations Own and scale the AI Developer Experience pillar, with an initial focus on measurably increasing shipped PRs per engineer per week through automation, and improving token efficiency as AI spend scales. Build the team from the ground up, converting today's borrowed, part-time contributors into a dedicated, full-time organization; the CTO has personally committed to reallocating direct reports and unlocking headcount. Run the build-vs-partner motion: stand up fast, structured engagements with third parties to benchmark, accelerate, and in some cases co-build: while defining objective eval criteria so decisions aren't subjective. Core workstreams: - NuContext: the knowledge and context-extraction layer (docs, Confluence, Jira, code) that everything else depends on; currently the single highest-priority area for Nu's long-term AI strategy. Owns ontology definition, context curation standards, knowledge graph traversal/retrieval, and context update mechanisms. - Vector (agentic coding & hosted environment): sandboxing, harness, memory/retrieval, and system-prompt optimization for AI-assisted coding. - Agentic Code Review: AI-assisted PR review to cut defect rates and cycle time, a direct lever on the org's top-line change failure rate (CFR) goal. - AI SRE:  moving from vendor evaluation to AI-native incident detection, diagnosis, and remediation at scale. - Prompt Classification & Model Routing and 3rd-party AI tooling vendor management: scope and placement still being finalized; the Director will help shape this boundary. - Longer term, the AI Enablement Platform (routing, marketplace, authentication) is expected to fold into this scope as leadership bandwidth allows. Qualifications Professional Experience & Education: - Proven leadership of AI-native developer tooling or platform teams, ideally at a company operating at meaningful engineering scale. - Track record building full-time, dedicated engineering teams out of fragmented, part-time, or borrowed resourcing: including experience in allocating teams, stellar in people leadership to do it without burning teams out. - Real experience structuring and running third-party vendor partnerships (evaluation, integration, managing lock-in risk) alongside first-party build. - Hands-on technical credibility in agentic coding systems, context/retrieval infrastructure, or developer-facing AI tooling: able to go deep with ICs, not just manage from a distance. - Comfort operating in a high-velocity, ambiguous, and high-executive-visibility organization; ability to align and mobilize teams to take on new challenges and scale impact. - High accountability and ownership mindset, coupled with the ability to move fast under pressure. - Comfort with an honest, unsolved problem space:  even leading peer companies are far from 100% AI-authored code; this role is about the challenge and the resourcing to attack it, not a pre-solved problem. - A track record that positions the Director as the natural next-step candidate for the broader Engineering Enablement M6 role. - A builder's instinct for evaluation rigor: experience designing evals/benchmarks that replace subjective quality judgments with objective, repeatable measurement. - Experience with sandboxed agentic execution environments, retrieval-augmented systems, or LLM-based code review tooling (nice-to-have). - Familiarity with token-cost management as AI spend scales (nice-to-have). - Prior exposure to fintech, regulated environments, or large legacy codebases where AI adoption is harder to get right (nice-to-have). Core Leadership Skills The following executive leadersh