• Own Automated Enforcement Quality: Serve as a strategic owner for enforcement outcomes across AI-driven systems. You will diagnose underperformance and make go/no-go recommendations on when models are ready for production. • Translate Policy Into Models: Act as the primary “policy-to-model” translator. You’ll craft prompts, define evaluation criteria, and curate high-quality datasets (“golden sets”) that teach models to distinguish between contextual debate and policy violations. • Guide Model Evolution: Monitor enforcement performance over time, identifying concept drift, policy changes, or emerging threats that require retraining, prompt updates, or evaluation redesign. • Surface Blind Spots: Develop monitoring strategies for niche communities, edge cases, and emerging behaviors to ensure enforcement systems reflect Reddit’s diversity and complexity. • Safeguard Model Integrity: Flag risks, escalate incidents, and recommend rollbacks or mitigations when automated systems fall below quality or safety thresholds, in partnership with ML and Product stakeholders.

• Operate autonomously to evaluate digital merchant tools and provide structured business data. • Independently testing newly deployed platform features, digital storefront tools, or AI recommendations designed for local business management and customer engagement. • Reviewing AI-generated business summaries, search visibility responses, and mapping integrations to verify empirical accuracy against actual business operations. • Providing comprehensive, audit-ready feedback detailing platform usability, relevance of digital tools, and practical day-to-day utility for local merchants. • Identifying and documenting specific instances where models misinterpret business categories, service offerings, operational hours, or local market nuances.

• Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution. • Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures). • Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. • Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. • Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning. • Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution.

• O Senior Microsoft AI Developer é responsável por projetar, desenvolver e evoluir soluções avançadas baseadas em IA, utilizando tecnologias Microsoft e Azure. • Essa função exige profundo conhecimento técnico, forte senso de ownership e capacidade de entregar soluções escaláveis de Generative AI em ambientes corporativos complexos. • O profissional atuará em estreita colaboração com times multifuncionais para projetar e implementar sistemas avançados de IA, incluindo frameworks multiagentes e soluções de automação inteligente, viabilizando transformação e inovação de negócios em escala. • Design, desenvolvimento e implementação de soluções de software baseadas em IA, utilizando Azure AI Foundry, Azure OpenAI e tecnologias Microsoft relacionadas. • Arquitetar e construir sistemas multiagentes e frameworks avançados de execução de tarefas com IA. • Projetar e integrar Graph connectors, plugins de API e Azure AI Search para suportar soluções corporativas inteligentes. • Traduzir requisitos complexos de negócio em arquiteturas técnicas escaláveis e seguras. • Atuar como responsável técnico pelas soluções, garantindo qualidade, performance, segurança e manutenibilidade. • Colaborar com times multidisciplinares (engenharia, produto, UX e stakeholders de negócio) para entregar resultados alinhados aos objetivos estratégicos. • Estabelecer e garantir boas práticas de engenharia, incluindo code reviews, documentação, estratégias de teste e padrões técnicos. • Investigar e resolver problemas complexos ao longo de todo o ciclo de vida do desenvolvimento de software. • Comunicar-se de forma clara com stakeholders técnicos e não técnicos, influenciando decisões e promovendo alinhamento. • Mentorar e apoiar outros engenheiros, contribuindo para a evolução técnica do time e melhoria contínua.