Staff AI Engineer

Experian

. Lead the strategy for the use and adoption of Artificial Intelligence across Marketing Services products .

Posted 10/22/2026full-timeRemote • São Paulo • BrazilLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the adoption of Artificial Intelligence in Marketing Services, with a strong focus on GenAI applications, RAG pipelines, and performance measurement. Proven ability to influence technical direction and mentor AI Engineers while establishing best practices and standards.

Highest-signal resume keywords

Artificial Intelligence StrategyGenAI ApplicationsRAG Pipeline DesignPython ProgrammingMachine Learning Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData AnalysisStatisticsRAGPrompt EngineeringFine-TuningTransfer LearningSQLLarge-Scale Data ManipulationGenerative Models Evaluation

Soft Skills

Technical LeadershipMentoringInfluencing Without AuthorityDocumentation SkillsCommunication

Tools & Technologies

OpenAI SDKLangChainCrewAIHugging FacePyTorchTensorFlowAWS Bedrock AgentsN8nFlowiseLangFlow

Industry Keywords

AI-Powered SolutionsDigital ProductsOperational EfficiencyAutomationJourney Acceleration

Tech Stack

Tools & technologies

AWSPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

Lead the strategy for the use and adoption of Artificial Intelligence across Marketing Services products
Conduct comparative experiments with different LLMs, agents, and GenAI architectures
Design, optimize, and evolve RAG pipelines, including chunking, embeddings, retrieval, and continuous evaluation
Establish evaluation and benchmarking frameworks for GenAI applications
Measure the performance, cost, and ROI of AI-powered solutions
Decide between Prompt Engineering, RAG, Fine-Tuning, and multi-agent architectures
Identify AI opportunities with Product, Engineering, Data, and Leadership teams
Translate technical results into recommendations for the roadmap, architecture, governance, and capabilities
Establish best practices, technical standards, and responsible GenAI usage
Build the applied AI vision for Marketing Services
Provide functional leadership to AI Engineers through technical direction, architecture reviews, mentoring, and documentation
Influence GenAI architecture and strategy decisions across multiple squads
Track production use cases, lead time, inference cost, component adoption, and BU autonomy

Requirements

What you’ll need

5+ years of experience in software engineering, data, or Machine Learning, with a track record of increasing technical responsibility
Proven experience leading technology transformation at the department, business unit, or organizational level, with measurable results
Experience establishing standards, components, or technical practices adopted by other teams
Proven experience taking GenAI solutions to production, using RAG and/or agents, with real users, ongoing support, and quality and cost measurement
Hands-on experience with GenAI and LLMs in a real-world business context
Experience designing, evaluating, and evolving solutions using RAG, embeddings, retrieval, and/or agents
Experience connecting AI to digital products, operational efficiency, automation, or journey acceleration
Advanced proficiency in Python
Strong knowledge of SQL and large-scale data manipulation
Solid foundation in statistics, data analysis, and experimentation
Experience evaluating generative models using traditional metrics and LLM-based approaches
Familiarity with the OpenAI SDK, LangChain, CrewAI, or equivalent tools
Experience building MCP (Model Context Protocol) servers
Ability to document trade-offs and turn technical conclusions into actionable recommendations
Experience developing engineers through mentoring and raising the technical bar
Ability to influence roadmaps and architecture decisions without formal authority
Advanced English proficiency is required for reading, writing, and conversation
Experience with Fine-Tuning, Transfer Learning, Hugging Face, PyTorch, or TensorFlow is a plus
Familiarity with AWS Bedrock Agents / AWS Agent Core is a plus
Experience with n8n, Flowise, LangFlow, or equivalent tools is a plus
Experience with Prompt Optimization, including DSPy or similar tools, is a plus

Benefits

Comp & perks

An inclusive culture and an environment that supports balancing your career with personal commitments and interests
Commitment to employee well-being
Opportunities for exceptional experiences and career growth
Great Place To Work™ recognition in 24 countries
International Top Employers certification
4.6 rating on Glassdoor