Staff AI Engineer

#### Company description Serasa Experian is the first and largest Datatech in Brazil. A leader in intelligence solutions for risk and opportunity analysis, focused on credit, authentication and fraud prevention journeys. With cutting-edge technology, innovation and the best talent, it turns the uncertainty of risk into the best decision, helping people achieve their dreams and companies of all sizes and sectors thrive. We have 22,000 people operating in 32 countries, and every day we are investing in new technologies, talented professionals and innovation to help all clients maximize every opportunity. With corporate headquarters in Dublin, Ireland, Experian is listed on the London Stock Exchange (EXPN) and is part of the FTSE 100 index. #### Job description We are looking for a Staff AI Engineer to lead the strategy for the use and adoption of Artificial Intelligence in Marketing Services products, combining deep technical expertise in GenAI with concrete product opportunities, operational efficiency and value creation for the BU. This is a senior individual contributor role: we expect you to build, decide and be accountable for what you put into production. In addition, you will functionally lead other AI Engineers, providing technical direction, reviewing architecture, setting standards and developing the team, without formal hierarchical management at this time. The position is central to the evolution of solutions based on LLMs, RAG and agents, and is responsible for identifying use cases, defining technical approaches and turning experimental learning into direction for Product, Engineering and Leadership. More than a reference in experimentation, we are looking for someone who has already applied AI to accelerate digital product strategies, improve journeys and support business decisions with real, measurable impact. #### Qualifications Main responsibilities - Conduct comparative experiments with different LLMs, agents and GenAI architectures applied to real business cases; - Design, optimize and evolve RAG pipelines, including chunking strategies, embeddings, retrieval and continuous evaluation; - Structure evaluation frameworks and benchmarking for GenAI applications, considering quality, relevance, reliability, cost, latency and alignment with the use case; - Measure performance, cost and ROI of AI-based solutions, supporting prioritization and scaling decisions; - Decide when to use Prompt Engineering, RAG, Fine-Tuning or multi-agent architectures, taking responsibility for the technical and business trade-offs of the choice; - Work in partnership with Product, Engineering, Data and Leadership teams to identify where AI can accelerate digital product strategies and increase value for the BU; - Translate technical results into clear recommendations for roadmap, architecture, governance and capability development; - Establish best practices, technical standards and responsible use of GenAI within the structure, with real adoption by the squads; - Build and lead the applied AI vision for Marketing Services, connecting technology trends to the real needs of clients, partners and products; - Raise the technical level of the team in GenAI through mentoring, architecture reviews and documentation of decisions. **Mandatory requirements** - 5+ years of experience in software engineering, data or Machine Learning, with a track record of growing technical responsibility; - Have led technology transformation at the scale of an area, BU or organization, able to describe the previous state, what changed and the measured result. Examples: adoption of AI or GenAI in products and teams, platform migration, MLOps program, architecture change or evolution of the engineering model; - Have established standards, components or technical practices adopted by teams other than your own, including how the adoption was achieved; - Proven experience taking GenAI solutions to production: RAG and/or agents with real users, ongoing support and measurement of quality and cost. Proofs of concept, notebooks or pilots that never reached users do not count; - Hands-on experience with GenAI and LLMs in a real business context; - Experience designing, evaluating and evolving solutions with RAG, embeddings, retrieval and/or agents; - Experience in initiatives that connected AI to digital products, operational efficiency, automation or journey acceleration; - Advanced proficiency in Python; - Solid knowledge of SQL and handling large volumes of data; - Consistent foundation in statistics, data analysis and experimentation; - Experience evaluating generative models, including traditional metrics and LLM-based approaches; - Familiarity with LLM frameworks and ecosystems, such as OpenAI SDK, LangChain, CrewAI or equivalents; - Experience building MCP (Model Context Protocol) servers, including tool design, exposure contracts and operation; - Ability to document trade-offs and turn technical conclusions into actionable recommendations. - Have developed engineers with observable growth: mentoring, ramp-up of new people on the topic, raising the team's technical level; - Have influenced roadmap and architecture decisions without formal authority, in contexts with conflicting interests; - Have driven a contested technical decision to adoption, and know what was needed to convince others, or what changed your position. **Languages** - Advanced English (mandatory): reading, writing and conversation for participation in global forums, committees and company-wide initiatives. Fluent English (a plus). **Nice to have** - Experience accelerating AI adoption within a Business Unit, connecting technology to strategy and execution; - Experience with digital products, personalization, automation, Martech or growth-oriented journeys; - Experience with Fine-Tuning, Transfer Learning, Hugging Face, PyTorch or TensorFlow; - Familiarity with AWS Bedrock Agents / AWS Agent Core; - Experience with automation and orchestration of GenAI workflows using n8n, Flowise, LangFlow or equivalents; - Experience with Prompt Optimization, including DSPy or similar approaches; - Experience coordinating a team or formal people management: the structure is expected to grow, and leading the team is a possible path for development; - Ability to move well between technical exploration and executive prioritization. **Expected competencies** - Decides with evidence. Supports technical choices with data, experiments and measurement, not with preference or authority; - Turns ambiguity into direction. Receives a poorly defined problem and returns a path with scope, risk and success criteria; - Communicates at both levels. Explains the same decision to an engineer and to an executive without losing precision or filling it with jargon; - Owns the outcome, not just the delivery. Follows what was built in production (quality, cost, incidents) and corrects course; - Separates hype from value. Recognizes when AI is not the answer and says so, even when the expectation is the opposite. **Expected scope** - Significant influence on GenAI architecture and strategy decisions, across multiple Marketing Services squads; - Technical reference for the BU's squads: standards, architecture reviews and raising the team's technical level; - Functional leadership of other AI Engineers, with technical direction and team development; - Active and measurable role in accelerating the pace of AI adoption in Marketing Services; - Connection between technical excellence and product and business direction. **How we will measure success** - GenAI use cases in production, built within the structure; - Reduction in lead time from idea to production; - Inference cost known, instrumented and optimized per use case; - Components and standards published and actually adopted by the squads; - BU autonomy in AI: less dependence on external queues to evolve the product. **What should set this profile apart** We are looking for someone who combines technical excellence in GenAI with an applied business vision, and who has already turned technical capability into real organizational change, not just a delivered project. The right person here reads the system, anticipates priorities, leads significant changes without formal authority, and moves the structure through technical direction and scalable standards. #### Additional information Serasa Experian is much more than you might imagine. With the purpose of creating a better future by expanding opportunities for people and businesses, we are more than 4,000 people in Brazil working across various teams and specialties. Here, every skill and diversity complements the others, and you can work on what you love most. We are committed to building an inclusive culture and an environment where people can balance their careers with their personal commitments and interests, with a focus on well-being. We work hard to be one of the best and most innovative companies to work for in the country, enabling incredible experiences and careers for our people. Our strong people-first approach is recognized externally through several market certifications: we have been awarded by Great Place To Work™ in 24 countries and by the international Top Employers certification, and we are recognized as one of the best companies for young professionals and have a 4.6 rating on Glassdoor. Each recognition tells us we are on the right path, providing an increasingly better work environment for our talent. Experian Careers - Creating a better tomorrow together [Find out what it's like to work for Experian by clicking here](https://www.experian.com/careers/)