• Establish and communicate an AI product strategy aligned with business priorities and growth objectives • Conduct market research, evaluate industry trends, and identify opportunities for AI within financial services • Translate business needs and user insights into clear product requirements and roadmaps • Partner with cross-functional teams to support the full product lifecycle, from concept through launch and ongoing enhancements • Promote responsible AI practices, including ethical considerations, governance, and transparency • Define and track key metrics to assess product performance and impact • Share product strategy, updates, and outcomes with leadership and stakeholders • Stay informed on developments in AI, machine learning, and related technologies, and assess their relevance to the organization • Support and guide teams in AI product practices, encouraging collaboration and knowledge sharing

Role Description If you've been operating as a Senior SEO Specialist or SEO Lead and want a move that expands your strategic visibility and exposure to AI-driven search, this role is built for you. As our first AI Search & Organic Growth Manager, you'll help shape how our GTM strategy navigates the shift from traditional search to AI-driven discovery (AI Overviews, Agentic, and LLM-based search). This role offers growth and leadership potential; you will not only drive our overarching AI search strategy but also build and lead your own dedicated team of SEO/GEO specialists. This is an ideal role for an ambitious professional who wants to grow into a true GEO specialist. You are someone who combines deep strategic thinking with hands-on technical execution, thrives in ambiguity, and knows how to transition a brand from legacy SEO traction to repeatable, AI-forward discovery growth. This role reports to the Marketing Director and is a crucial part of the GTM strategy. What You’ll Own - Planning and Management of SEO & GEO Campaigns - Develop a comprehensive organic SEO and GEO strategy for the Scoop website, including a roadmap of initiatives to drive growth. - Perform research to gain a better understanding of target audience, brand, category, and competitive landscape. - Conduct thematic research to generate relevant content themes for new and existing programs. - Conduct regular technical SEO audits to identify and resolve issues related to site architecture, crawlability, indexation, page speed, and structured data, partnering with engineering teams to implement fixes. - Structure content for LLM ingestion, including entity optimization, semantic markup, schema.org structured data, and authoritative citations. - Understand customer search and AI discovery behavior and provide guidance to internal content teams to help them meet customers where they are. - Enhance on-page optimization of pages based on keyword research and program goals, as well as off-page tactics including article syndication with respect to domain authority enhancement. - Ensure campaign errors and issues are troubleshot and resolved in a timely manner or escalated as necessary. - Optimization - Suggest and implement content improvements with a view to improving organic traction. - Identify and provide recommendations on how to improve organic visibility inside Large Language Models (LLMs). - Develop and implement link and traffic building strategies. - Analysis & Measurement - Monitor key metrics to assess opportunities and issues for both search engines and LLMs, regularly presenting findings to the Marketing team. - Monitor and optimize how Scoop’s content surfaces in AI chatbots such as ChatGPT, Perplexity, and Google AI Overviews, including tracking citations and visibility. - Monitor and measure brand visibility in generative engine responses using dedicated GEO tools, such as Otterly.ai, SEMrush AI Overview Tracker, etc. - Operational Excellence & Industry Knowledge - Partner closely with leadership to strengthen internal processes, documentation standards, and delivery frameworks. - Manage dedicated SEO tools (such as Google Search Console, SEMRush, Sistrix, Screaming Frog) and identify and onboard new tools as needed. - Keep updated on the search marketing industry by researching, networking, reading blogs, forums, and new sources. - Share knowledge of advanced SEO/GEO practices into the business to assist in the development. What Success Looks Like - Meaningful increase in organic traction and brand footprint across both traditional search engines and AI generative engines. - A predictable, data-driven tracking and reporting framework for AI citations and chatbot visibility. - Successful deployment of an optimized technical content architecture engineered for seamless LLM ingestion and agentic discovery. - Establishment of clear internal workflows, documentation standards, and process optimization frameworks. Qualifications - 3-5+ years of SEO experience, ideally within an agency or startup environment. - Proven track record of owning organic visibility KPIs, technical strategy, and delivering measurable outcomes. - Strong hands-on expertise in technical SEO, content strategy, and analytics platforms (GA4, GSC, Adobe, Looker Data Studio, or similar) — be ready to walk us through a specific technical audit or migration you led. - Hands-on experience adapting strategy for AI-driven search — generative engines, AI Overviews, LLM-based discovery, agentic discovery. - Strong project management skills; able to juggle multiple projects, timelines, and priorities. - Comfortable operating with high autonomy as an elite individual contributor—strategic but deeply hands-on. - Data-driven, organized, and highly accountable. - Fluent in English. How You Work (Aligned with Scoop Values) - You bring strong structure, organization, and process to drive productivity and results. - You take initiative and implement innovative approaches to growth. - You communicate clearly and collaborate effectively across teams. - You act with urgency and consistently follow through on commitments. - You demonstrate strong ownership, integrity, and accountability. Application Note You’ve actually read this job description! In your application, tell us one thing about AI-driven search you’ve tested or implemented in the last six months. Generic cover letters get filtered out. Please apply with an English resume. Compensation and Benefits - Competitive compensation based on a variety of factors, including relevant experience, knowledge, and skills. - Monthly Compensation: R$ 15.000 – R$ 20.000 / month - Contract Type: PJ (Independent Contractor / Prestação de Serviços) - Within the posted range, individual compensation is determined by a variety of factors, including specific work experience, relevant skills, certifications, and geographic location. We are committed to pay equity and regularly review our compensation structures to ensure fairness. - Fully remote work from a fixed home office. - Professional development opportunities. - Collaborative and innovative work environment. Why Join Scoop - Strong product-market fit with clear growth opportunity. - Solid marketing foundation ready to be scaled with next-generation search capabilities. - High ownership and visibility across the business. - Opportunity to build, shape, and directly lead the next phase of organic discovery growth.

• Own the architectural vision and technical roadmap for Intelligence (data, learning, reasoning) and Agentic interfaces, workflows • Design and evolve agent-based workflows, enabling reasoning-capable, adaptive, multi-step systems with strong trust patterns (grounding, evals, confidence scoring) • Develop and drive evaluation frameworks measuring model quality, agent reliability, drift, and platform effectiveness • Make AI workloads observable to engineering and product • Architect for simplify the core, customize at the edge • AI/ML capabilities are opinionated at the center, with foundations for marketplace or platform-exchange patterns at the edge • Architect agentic UX and enable just-in-time interfaces • Build evaluation frameworks: model quality, agent reliability, drift detection, eval harnesses, observability for AI workloads • Set engineering standards through working reference implementations, in-repo templates, and patterns AI/ML teams can copy • Lead the polyglot AI stack: vector search, embeddings pipelines, RAG architectures, agent frameworks, model lifecycle, MLOps • Drive AI-augmented engineering practice • Personally set the bar • Engage directly with customer-facing teams and customers to ground AI architectural decisions in real workflows • Mentor engineers; raise the technical bar through code review, design review, and technical coaching.

• Develop and implement agentic AI solutions using agent-based architectures, multi-agent systems, and advanced language models. • Design autonomous agents capable of: - Planning and executing complex tasks; - Using external tools (tool calling); - Consuming APIs and integrating with various enterprise systems; - Making decisions based on context and defined objectives. • Build intelligent assistants and specialized agents for: - Implementing different RAG (Retrieval-Augmented Generation) strategies; - Process automation; - Decision support; - Generating insights and content; - Conversational interaction and customer-facing experiences. • Design and implement advanced GenAI pipelines including: - Different RAG (Retrieval-Augmented Generation) strategies; - Integration with structured and unstructured knowledge bases; - Contextual memory strategies and history management; - Use of vector databases and knowledge graphs. • Work with modern frameworks for developing intelligent agents such as: - LangChain; - LangGraph; - CrewAI; - AutoGen; - Semantic Kernel; - Other emerging frameworks. • Develop and implement LLMOps/AgentOps practices, including: - Monitoring; - Evaluation; - Observability; - Versioning; - Traceability; - Governance of models and agents. • Prototype Python applications integrated with AI services, automations, and cloud ecosystems. • Research and explore new architectures, techniques, and trends related to agentic AI and multimodal models. • Collaborate with data scientists, data engineers, developers, and stakeholders in multidisciplinary squads. • Document solutions, patterns, and learnings, contributing to the team’s technical evolution.