• Desenvolver e implementar soluções de **IA Agêntica**, utilizando arquiteturas baseadas em agentes inteligentes, sistemas multiagentes e modelos de linguagem avançados. • Projetar agentes autônomos capazes de: - Planejar e executar tarefas complexas; - Utilizar ferramentas externas (tool calling); - Consumir APIs e integrar diferentes sistemas corporativos; - Tomar decisões baseadas em contexto e objetivos definidos. • Construir assistentes inteligentes e agentes especializados para: - Utilização de diferentes estratégias de RAG (Retrieval-Augmented Generation). - Automação de processos; - Apoio à tomada de decisão; - Geração de insights e conteúdo; - Atendimento e interação conversacional. • Projetar e implementar pipelines avançados de GenAI incluindo: - Diferentes estratégias de **RAG (Retrieval-Augmented Generation)**; - Integração com bases de conhecimento estruturadas e não estruturadas; - Estratégias de memória contextual e gerenciamento de histórico; - Uso de bases vetoriais e grafos de conhecimento. • Trabalhar com frameworks modernos para desenvolvimento de agentes inteligentes como: - LangChain; - LangGraph; - CrewAI; - AutoGen; - Semantic Kernel; - Outros frameworks emergentes. • Desenvolver e implementar práticas de **LLMOps/AgentOps**, incluindo: - Monitoramento; - Avaliação; - Observabilidade; - Versionamento; - Rastreabilidade; - Governança de modelos e agentes. • Prototipar aplicações em Python integradas a serviços de IA, automações e ecossistemas cloud. • Pesquisar e explorar novas arquiteturas, técnicas e tendências relacionadas à IA Agêntica e modelos multimodais. • Colaborar com cientistas de dados, engenheiros de dados, desenvolvedores e stakeholders em squads multidisciplinares. • Documentar soluções, padrões e aprendizados, contribuindo para a evolução técnica do time.

• Own the vision, strategy, and multi-quarter roadmap for agentic AI solutions that improve bank decisioning outcomes (e.g., fraud/financial crime, credit decisioning, marketing next-best-action, collections, servicing). • Lead the AI Modeling Platform (AMP) as a product by defining capabilities, prioritizing features, and ensuring reusable components (decision agents, tool use, orchestration, evaluation, monitoring) that accelerate delivery across lines of business. • Translate business problems into measurable value cases (loss reduction, approval rate lift, fraud capture, cost-to-serve reduction, customer conversion lift) and track benefits realization. • Establish standards for agent safety, governance, and controls appropriate for regulated banking use (human-in-the-loop, auditability, model/agent documentation, monitoring and escalation playbooks). • Lead and grow a team of data scientists / ML engineers / decision scientists building agentic solutions end-to-end (prototype → production). • Coach team members in agentic AI patterns (planning, tool-use, RAG, workflow orchestration, multi-agent collaboration), and in bank decision science fundamentals (risk, uplift modeling, scorecards, optimization, experimentation). • Build a sustainable talent pipeline through hiring, onboarding, career development, and performance management; create an inclusive culture of high standards, continuous learning, and operational excellence. • Drive end-to-end Agile delivery from discovery through scaling and lifecycle management, ensuring production-grade performance (reliability, latency, cost, security/privacy, resiliency, monitoring) and rigorous agent evaluation controls (test suites, red-teaming, guardrails, bias/fairness, drift, incident response). • Drive enterprise partnership and scale by aligning cross-functional stakeholders (Fraud/FC, Credit Risk, Marketing, Collections/Servicing, Data/Engineering, Model Risk, Compliance/Legal, InfoSec, Ops) and cross-region teams (US/IAH) around the platform value proposition to enable adoption and reuse at scale. • Stay ahead of agentic AI/LLMOps and regulatory/MRM trends and use that expertise to consult with stakeholders to identify high-impact decision opportunities, co-design solutions, align success metrics, secure resources, and convert best practices into actionable standards for AMP and delivery teams.

Role Description Origin is seeking an AI-Native Marketer who utilizes automation, AI systems, and modern tooling to operate with exceptional speed and leverage. You will own campaigns end-to-end, from positioning and messaging to content, acquisition, and attribution. This is a highly hands-on role for someone who can both think strategically and execute quickly. You’ll work across brand, growth, product marketing, and demand generation, using AI to scale output without sacrificing quality or technical credibility. You’ll help define how Origin shows up to the market while building the systems, workflows, and experimentation culture that power our growth. You’ll have meaningful influence over the company’s positioning, voice, and go-to-market motion as we scale. Responsibilities - Build AI-powered marketing workflows for content creation, segmentation, personalization, lifecycle marketing, and reporting. - Execute campaigns across paid, organic, email, events, and partnerships. - Develop prompt libraries, editorial standards, and evaluation frameworks that maintain a high quality bar. - Run rapid messaging and content experiments across channels. - Create technically credible content for security and infrastructure audiences. - Partner with RevOps and Sales to improve attribution, reporting, and pipeline visibility. - Maintain and optimize the marketing stack while continuously evaluating new tooling. - Help internal teams understand how AI can improve operational leverage. Qualifications - 3+ years in B2B SaaS marketing across growth, content, product marketing, or operations. - Strong hands-on experience with LLMs, AI workflows, and automation tooling. - Comfortable building landing pages, lightweight apps, and automations independently. - Excellent writing instincts and editorial judgment. - Strong analytical skills with experience using attribution and reporting tools. - Systems-oriented mindset with a bias toward experimentation. - Comfortable operating in ambiguity and helping define the function as you go. Nice to Haves - Experience marketing cybersecurity or infrastructure products. - Early-stage startup experience. - Familiarity with AI/ML concepts and technical security topics. Benefits - Generous healthcare. - Flexible PTO. - Home-office support. Company Description Origin is a fully remote team across the US & Canada, built on trust, autonomy, and excellence. We empower our team to take ownership, move with purpose, and continuously improve. Our culture values top performers who align with our mission and embrace high standards. While we move fast, we prioritize quality, collaboration, and remain committed to building impactful security solutions with precision.

• Build AI-powered marketing workflows for content creation, segmentation, personalization, lifecycle marketing, and reporting. • Execute campaigns across paid, organic, email, events, and partnerships. • Develop prompt libraries, editorial standards, and evaluation frameworks that maintain a high quality bar. • Run rapid messaging and content experiments across channels. • Create technically credible content for security and infrastructure audiences. • Partner with RevOps and Sales to improve attribution, reporting, and pipeline visibility. • Maintain and optimize the marketing stack while continuously evaluating new tooling. • Help internal teams understand how AI can improve operational leverage.