• Projetar, desenvolver e implementar agentes de IA focados em soluções de segurança, utilizando frameworks e ferramentas líderes do mercado; • Integrar e operacionalizar modelos de linguagem de grande porte (LLMs) e bases de conhecimento, automatizando e otimizando processos críticos através de Python e APIs modernas; • Avaliar e sugerir alternativas em plataformas de GenAI (como AWS Bedrock, Azure AI, Google Vertex AI) para criação customizada de agentes inteligentes, considerando aspectos de escalabilidade e segurança; • Implementar e consultar bancos de dados vetorizados (ex: Pinecone, Weaviate, Milvus, ChromaDB) para garantir armazenamento e recuperação eficiente de informações; • Atuar como advocate de IA, promovendo treinamentos, talks e compartilhando boas práticas de segurança em IA para outros times de desenvolvimento; • Automatizar processos de deploy e monitoramento de agentes e modelos em ambientes cloud, utilizando ferramentas como Docker, Kubernetes, Terraform e CI/CD.

• Drive AI Adoption and Business Enablement: Lead the rollout and adoption of AI solutions across the European region. • Coordinate Regional AI Operations: Act as the key liaison between headquarters, regional teams, and distributors. • Monitor Performance and Drive Continuous Improvement: Track AI adoption, user engagement, and operational performance metrics. • Support Cross-Functional Collaboration: Work closely with Product, Technology, Sales, and Operations teams to communicate market needs and user feedback.

• Own end-to-end execution of AI and automation POCs, from idea to validation • Rapidly test tools, frameworks, and agentic workflows to solve business problems • Iterate quickly prioritize speed, learning, and business impact over perfection • Design and implement agentic workflows using modern AI tools (LLMs, copilots, automation platforms) • Identify opportunities to automate repetitive or manual processes across teams • Continuously refine workflows to improve efficiency and scalability • Act as the bridge between business teams and technical teams • Translate business pain points into actionable AI use cases • Partner closely with DevOps to ensure solutions are practical, secure, and cost-effective • Define and track KPIs for AI initiatives (e.g., time savings, cost reduction, adoption) • Support leadership and Board-level visibility into AI initiatives and impact • Evaluate tools and architectures with a strong focus on cost efficiency • Make decisions on build vs. buy vs. integrate approaches • Collaborate with dedicated DevOps resources to optimize deployments • Highly proactive and self-driven • Comfortable operating in ambiguity and fast iteration cycles • Strong communicator who can influence across teams • Focused on business impact, not just technical output.

• Own the full lifecycle of Code for America's AI Acceptable Use Policy: drafting foundational policy from the ground up, socializing it across the organization, driving adoption, and revising it on an ongoing basis as tools, risks, and best practices evolve • Advise on the employee-facing implications of AI tool deployment, including acceptable use boundaries, monitoring practices, and policy provisions that intersect with employment law and workforce relations — working in close coordination with People Operations and Legal. • Write governance frameworks and policy documents in accessible, plain-language formats — ensuring that staff at all levels and across all disciplines can understand and act on guidance, not just compliance and IT teams • Serve as an internal consultant to teams in the early stages of exploring, piloting, or refining AI-assisted workflows — guiding experimentation with a "yes, and here's how to do it safely" orientation • Document and share learnings from team-level pilots to build organizational knowledge and surface replicable patterns • Act as a liaison between IT/security and non-technical program and operations teams, translating between contexts and representing staff needs when governance or tooling decisions are being made • Partner with People Operations and Legal on the development and ongoing review of AI-related employment policies, including policies that govern employee conduct, monitoring, and use of AI tools in the workplace — ensuring governance frameworks are informed by and aligned to employee relations considerations. • Lead change management for AI-related transitions — helping staff understand not just what is changing, but why, and what it means for their work • Partner closely with Security Engineering to ensure AI governance and enablement work is integrated with the organization's broader security posture • Collaborate with compliance stakeholders and legal/People Operations as needed to assess AI tool risk, data privacy implications, and organizational policy alignment— including implications for employee relations and workforce obligations. • Monitor the evolving AI governance and security landscape and proactively recommend policy and control updates as new tools, risks, or regulations emerge • Maintain the vendor inventory, conduct lightweight third-party security reviews on new tools, and escalate higher-risk reviews to the Security Engineering team • Coordinate security awareness programming, including staff training and onboarding modules • Design, launch, and continuously improve a suite of AI enablement resources: training sessions, onboarding guides, office hours, self-serve resource hubs, and practical playbooks • Facilitate workshops and learning sessions for staff across all levels and disciplines, explaining technical concepts in accessible, jargon-free ways • Build and steward an internal AI Champions network — recruiting, supporting, and coordinating peer advocates across departments to drive adoption and share learnings • Develop onboarding materials for new staff and role-specific enablement resources for teams with specialized AI use cases • Other duties as assigned