Engineering Manager, Enterprise Solutions - Latin America

About

We help global enterprise partners integrate Meta's foundation models and AI tools directly into their core products and infrastructure. We are looking for a hands-on Engineering Manager to build and lead our Latin America software engineering team and shape how Enterprise Solutions deploys, and scales, AI agents in the field across the region. Anchored in Brazil, our must-win market, you will stand up the in-region team from the ground up, directly manage the software engineers who build inside client environments, own the engineering craft and delivery of multiple concurrent enterprise deployments, and partner across Product, Data Engineering, Business Engineering, Sales, and our NORAM and APAC engineering leadership to keep one coordinated global motion. This is a player-coach role, roughly 80% people leadership and coaching and 20% hands-on. You hold a high bar for technical rigor and land code regularly, enough reps to coach and hold the team accountable, but you are not in the critical path for delivery (not a TLM load). You are the dedicated Latin America engineering leader. Our NORAM-based team currently covers the live Brazil engagements via travel and rotations; you will take them over durably and build real in-region capacity, starting with a Brazil-anchored pod and expanding to Spanish-speaking Latin America over time. This is a ground-floor build: comfort operating in ambiguity, and building structure where there is none, is essential.

Responsibilities

• Hire, manage, and grow the Latin America software engineering team from the ground up, starting by recruiting a senior architect (IC6 SWE) as the technical anchor and then filling the remaining engineer and pod seats. Set clear expectations and goals, give timely and candid feedback, and proactively manage performance
• Build the in-region talent pipeline. Recruit exceptional operator-engineers (builders with a founder's mindset, not back-office SWE profiles); source from consulting and delivery firms (for example Accenture, Deloitte, Globant) and the local startup ecosystem, and sell the mission to top candidates in a newly formed, fast-moving org
• Assess whether and when sub-team structure or additional managers are warranted as the org scales, and propose it. We default to lean spans and add structure only where it earns its keep
• Assess whether and when sub-team structure or additional managers are warranted as the org scales, and propose it
• Own team health (Pulse, retention, upward feedback) and a culture of psychological safety, ownership, and accountability
• Stay technical: drop into client co-builds, review deployment architecture, and contribute outside of the critical path. Use AI to extend your team's reach across disciplines
• Ensure sound, expedient technical decisions with high craft across connectors, integrations, agent tuning, evals, and the agentic runtime
• Uphold the IP-separation operating model: engineers build connectors, endpoints, and reusable tooling and do not modify client core code; reusable assets stay separable (separate repos, OSS/copyleft scanning)
• Your strong engineering capability will lead to the runbooks, recipes, and reusable assets compound and each engagement to be faster than the last
• Own engineering delivery across multiple concurrent forward-deployed engagements, starting with the Brazil flagship engagements; balance speed-to-value, quality, and reliability through the deployment lifecycle (Use Case Discovery, Tech Discovery, Build and Hill-climb, Pilot, Production, Expand or Transition)
• Optimize for durable, quantified proof points on the levers where Meta genuinely wins (native in-thread capabilities, privileged placement, Paid Messaging interop), not just feature parity with third-party agents
• Make decisions that maximize impact while minimizing cost in people, time, and tokens; identify where AI automation increases team scope and cuts deployment effort
• Manage the Latin America forward-deployed and in-region software engineers, anchored in Sao Paulo for Portuguese-speaking LATAM, with a Spanish-speaking pod based in Sao Paulo or Argentina
• Partner with the NORAM engineering leader, who bridges the Brazil engagements until your team is in place, and with APAC Product Engineering leadership, so every pod runs the same playbooks and feeds the same global rhythm of business
• Partner with Business Engineering (operated as one shared talent pool with Enterprise Solutions, with existing presence in Sao Paulo), Product, Data Engineering, and Sales so deployments land seamlessly and invisibly to the customer

Minimum Qualifications

• 8+ years of software engineering experience, including hands-on technical contribution
• 4+ years of engineering management experience, including managing teams with technical leaders or other managers
• Experience driving technical strategy and roadmap planning across multiple concurrent large-scale software projects
• Experience recruiting, developing, and retaining engineering talent, including performance management of leaders
• Experience partnering cross-functionally with product, design, and data science to define requirements and deliver software at scale Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience as, or managing, forward-deployed engineers or solutions architects (building in customer environments)
• Experience standing up new teams or in-region engineering, and building structure in newly formed orgs
• Background in AI/ML systems, agent architectures, integrations/connectors, or platform engineering (e.g., production Python/TypeScript, data pipelines, vector databases, RAG, multi-step agentic workflows)
• Enterprise or B2B deployment experience, especially in regulated or data-sensitive contexts
• Professional fluency in Spanish, to serve Spanish-speaking Latin America (Argentina, Chile, Colombia) as the hub expands beyond Brazil
• An existing network in the Latin American engineering or startup community to accelerate hiring
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Familiarity with Meta's engineering stack and practices