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Why this grade This listing scored 46/100, which is a D. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 12 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-5 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$163k – $276k
That is the middle half of what comparable roles paid on this board over the last 90 days — 31 listings that did publish a figure, median $179k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
Data Science Mid level Full Time
Estamos em busca de um(a) AI Engineer (GenAI Platform) para atuar na evolução da nossa plataforma global de Inteligência Artificial Generativa.
Essa posição terá papel fundamental no design, desenvolvimento e operação de serviços de IA que suportam times de engenharia e produto em diversos países, permitindo a criação de soluções baseadas em GenAI de forma escalável, segura, observável e eficiente em custos.
O foco da função é o desenvolvimento de capacidades de IA Generativa em nível de plataforma, incluindo sistemas agentic, integração de modelos, LLMOps e governança de custos. Não se trata de uma posição voltada para treinamento ou fine-tuning de modelos do zero.
Principais responsabilidades
- Projetar e desenvolver serviços de IA Generativa e sistemas multiagentes.
- Implementar soluções de RAG (Retrieval-Augmented Generation), tool-calling e orquestração de agentes.
- Integrar e operar modelos através de gateways LLM.
- Desenvolver práticas de LLMOps para monitoramento, observabilidade e governança.
- Implementar mecanismos de medição de consumo, chargeback e otimização de custos de inferência.
- Construir e manter pipelines de dados que suportem processos de billing e metering.
- Aplicar práticas de MLOps, CI/CD, testes automatizados e gestão de ciclo de vida de modelos.
- Atuar em incidentes, monitoramento, confiabilidade e melhoria contínua dos serviços.
- Colaborar com times globais de Produto, Engenharia, Plataforma, Segurança e Dados.
Requisitos obrigatórios
- Experiência em Engenharia de Software e IA Aplicada.
- Experiência prática em projetos de GenAI em ambiente produtivo.
- Inglês avançado.
Conhecimentos técnicos em:
GenAI e Agentic AI
- Multi-agent orchestration
- Tool calling
- Multi-step reasoning
- RAG
- Prompt Engineering
- LangChain, LangGraph ou frameworks equivalentes
LLMOps e Plataformas
- Gateways LLM (LiteLLM ou similares)
- Integração de modelos via APIs
- Observabilidade
- Avaliação de aplicações baseadas em LLM
- Otimização de latência e performance
- Vector databases e mecanismos de retrieval
Linguagens e Cloud
- Python avançado
- AWS (preferencial)
- Boas práticas de arquitetura, observabilidade e reprodutibilidade
MLOps
- Versionamento e rastreamento de experimentos
- CI/CD
- Testes automatizados
- Deployment e rollback de serviços de IA
Data Engineering
- Conhecimento em pipelines de dados
- Batch e streaming
- Spark e arquiteturas Lakehouse
- Orquestração de dados
Diferenciais
- Kafka e Event Streaming
- Terraform e Infrastructure as Code
- Databricks (Delta Lake e DLT)
- Experiência com plataformas internas para desenvolvedores
- Atuação em ambientes globais e distribuídos
At Serasa Experian, we believe that diversity is essential for a healthier and more innovative work environment, where everyone can share experiences and express their ideas. That’s why we promote several initiatives to support inclusive recruitment and the professional development of our people.
We also have our affinity groups, created to empower and support individuals from underrepresented groups: ExperianPride (LGBTQIAPN+ community), Ubuntu (racial equity), Women in Experian (gender equity), Aspire (people with disabilities), and Connecting Generations (generations).
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
Experian is a global data and technology company that powers opportunities for people and businesses around the world. We operate across a wide range of markets, including financial services, healthcare, automotive, agribusiness, insurance, among others. Experian invests in people and in advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees across 32 countries.
Our uniqueness is valuing yours. Experian’s people-centric, inclusive, and purpose-driven culture has been recognized with several awards — including World’s Best Workplaces™ 2025 (Fortune Global Top 25) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers site to understand why. Experian is also proud to be an equal opportunity and affirmative action employer.
Originally posted on Himalayas
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Where this listing came from
- 18 Sep 2026 Himalayas first sighting
Seen on 1 board over 0 days.