ALAC (Latin America) Sales AI Strategy & Architecture Lead

Apple

1d•Onsite

About The Position

The ALAC Sales — AI Strategy & Architecture Lead is a senior strategic and technical leadership role connecting AI and Sales at enterprise scale, based in São Paulo. This AI practice is purpose-built to serve the ALAC Sales organization, applying AI to drive Sales outcomes at regional scale. This role will design the technical architecture for ALAC's AI solutions —from technology selection and system integration patterns to agentic orchestration and deployment topology— while leading cross-functional teams spanning data quality & governance, AI business enablement, and agentic engineering. Architect enterprise-scale multi-agent systems, function-specific AI tools, and the full agent development lifecycle. Partners with IS&T, Legal, business teams, and executive leadership to translate Sales challenges into high-impact AI solutions. This role requires a hands-on leader. At Apple, people managers work alongside their teams, contributing directly to the work, not only directing it, as Apple operates with intentionally lean team structures.

Requirements

8+ years of relevant work experience
5+ years in a leadership role
Fluent in English and Portuguese
Hands-on contributor mindset — comfortable doing the work alongside a lean team, not only directing it
Experience leading blended teams (internal + contractors)
Proven experience designing and delivering enterprise
Proficient with AI/ML solution architectures — including technology selection, integration
Cloud data platforms (Databricks, Snowflake, BigQuery, AWS/GCP/Azure)
ML/AI frameworks and model productionization
Data governance frameworks (LGPD, GDPR, DAMA- DMBOK) — LGPD compliance experience strongly preferred
Regional or multi-country organizational experience

Nice To Haves

Master's degree
Spanish proficiency
Prior experience building an AI practice, Center of Excellence, or applied AI team from the ground up

Responsibilities

Define and execute the overarching data and AI strategy for the ALAC Sales organization
Align initiatives with Sales business objectives, focusing resources on highest-impact projects
Shape the AI practice operating model across practice areas, adapting as the field evolves
Design end-to-end solution architectures for ALAC AI initiatives — from technology selection and system integration patterns to data flow design, deployment topology, and build-vs-buy evaluation
Architect enterprise-scale multi-agent systems for ALAC — defining their internal structure, tool integrations, memory systems, and interaction patterns across workflow automation and decision support
Design and define orchestration architecture across agents and multi-agent systems developed internally and by other Apple areas, authoring technical design proposals and reference architectures that guide engineering execution
Design function-specific AI tools and interfaces — purpose-built agentic environments tailored to each Sales role, from UX patterns to backend integration
Own the full agent development lifecycle —from architecture and training to orchestration, versioning, and continuous improvement— while the AI Business Process Champion owns the business-side functional specifications that define what each tool should do from the user's perspective
Partner with IS&T, Legal, business teams, and Executive leadership
Translate business problems into technical requirements and technical outcomes into business insights
Coordinate with other Apple areas on shared agent and multi-agent ecosystems
Champion data privacy, security, governance, and ethical AI across the organization
Set data quality strategy, standards, and governance policies — with execution and operationalization owned by the AIML Data Quality and Governance Scientist — and ensure regulatory compliance (including LGPD)
Extend governance to the agentic layer — auditable agent definitions, version history, and improvement roadmaps
Manage project portfolios balancing rapid prototyping with production-grade delivery
Oversee agentic system and AI tool deployments with measurable adoption outcomes
Build and lead teams across practice areas —currently including data governance, AI business enablement, and agentic engineering— with both internal staff and contractors
Hire, coach, and develop team members; set performance expectations and career paths
Define AI practice operating cadences, collaboration norms, and contractor delivery standards.