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Job Description: AI & Data – AI ManagerLocation:Buenos Aires (Hybrid)Clients:US-based Enterprise ClientsAbout the RoleThe AI Manager leads technical strategy, oversees AI/ML engineering teams, and ensures high governance standards across enterprise AI programs. This role combines leadership, architecture, and cross-functional alignment.Key ResponsibilitiesLead AI technical strategy, architectural decisions, design and roadmap execution of AI initiatives.Oversee engineering teams delivering AI/ML and LLM-based solutions at scale.Define and enforce technical standards, governance, and responsible AI practices.Partner with business and technical stakeholders to align AI initiatives with organizational goals.Provide coaching, mentorship, and development for AI engineers.Skills & QualificationsPython & DevelopmentStrong Python (+5 years)Technical leadership; Code reviews;Microservices architecture; Definition of technical standardsPreferred: Performance optimization; legacy-to-AI-platform migrations; Distributed systems designWe evaluate: Technical decisions; scalability; mentoring/coaching; standardsLLMs, RAG& Agents:Enterprise LLM design leadership; Governance, policies & risks; Strategy for RAG and agents; Continuous evaluation pipelinesPreferred: Model/vendor selection (Azure/OpenAI/Anthropic/Mistral)What we evaluate:



Strategy; risks; compliance; cost/safety criteriaAgent OrchestationAgent observability; LangchainPreferred: Langraph, autogenCloud (Azure or Databricks):Azure: Cloud architecture (security, networking, cost management, DRP); multi-cloud; AI landing zones.Databricks: Lakehouse governance & design; Lineage; granular permissions; Multi-workspace integration.Preferred: Cross-cloud residency/compliance, Cost strategy & optimizationWhat we evaluate: Compliance; standards; scalability. Standardization; architectural decisions; cost controlMLOps & Delivery:Enterprise MLOps strategy; Model governance;AI SLAs (latency, grounding, costs); AI FinOps;Integration with client Data GovernancePreferred: Hybrid MLOps (on - prem + cloud)What we evaluate: Operation at scale; security; cost controlML Fundamentals:Strategic model decisions for AI productsPreferred: Model risk evaluationWhat we evaluate: Impact-driven judgmentAI Factory Design:Cloud/vendor selection; AI infrastructure evaluation (model catalogs, vector DBs, observability); Tooling choices (Databricks, Azure AI Studio, OpenAI, Anthropic); End-to-end governancePreferred: Adoption roadmap; reference playbooks; maturity metricsWhat we evaluate: Vision; ecosystem orchestration; risk & complianceCommunication and other requirements:C1 english executive communicationGlobal stakeholder managementBachelor degreePreferred: Cross-cultural leadership

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📌 Manager Ai Engineer - Ey Gds (Buenos Aires)
🏢 Ernst & Young
📍 Buenos Aires