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[Job - 32565] AI Engineer Senior, Brazil

CI&T · Brazil · Remote

  • IT Services & Consulting
  • 5,001–10,000 employees
  • New York, NY

Strong hiring record · median 22 days open

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Actively hiring

Posted today · still listed on the employer's own board · How we score

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  • Posted today
  • Still listed on the employer's own board

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[Job - 32565] AI Engineer Senior, Brazil at CI&T. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.

With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.

We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.

As CI&T grows its Data & Analytics Center of Excellence, we seek a talented and experienced Graph Database Developer to join a specialized team building an AI-powered fashion advisory platform for a leading client in the fashion and retail industry. This role is central to turning unstructured editorial content into a structured knowledge graph that powers real-time, intelligent style recommendations for end users attending formal events.

The Graph Database Developer will work in a staff augmentation model, integrating with a cross-functional team that includes a Machine Learning Developer and a GenAI Agent Developer. This is a hands-on technical position requiring strong ownership of the graph data layer — from schema design through ingestion, entity resolution, and query performance — with direct impact on what the AI agent recommends to users.

Responsibilities

Schema Design

Define node labels and edge types that represent the relationships between designers, garments, style attributes, trends, occasions, and editorial articles.

Entity Ingestion

Build workflows that consume structured JSON payloads from the upstream data pipeline and load them into the graph database in batch mode.

Probabilistic Entity Matching

Match extracted item mentions (for example, a bag described by type, color, and material) to the correct product node in a catalog of 50,000+ SKUs by scoring attribute overlap, assigning a match confidence, and creating the relationship only when it exceeds a defined threshold. Deduplicate items that appear inconsistently across different articles.

Editorial Signal Weighting

Assign weights to relationships based on how prominently an item or trend was featured, distinguishing a dedicated feature from a passing mention. These weights determine what the AI agent surfaces first in its recommendations.

Query Optimization

Design and tune openCypher traversal queries, including multi-hop queries, to return relevant results in under three seconds for downstream Amazon Bedrock Agents.

Cross-Functional Collaboration

Work alongside the Machine Learning Developer and GenAI Agent Developer to align the graph structure with the retrieval and recommendation needs of the AI agent.

Technical Validation

Support technical interviews and validation of new team members joining the graph database workstream, as needed.

Requirements

Advanced English proficiency (C1 or above), with autonomy to communicate directly with international stakeholders

Solid experience with the property graph data model

Experience writing and optimizing openCypher queries, including multi-hop traversals under latency constraints

Experience designing graph schemas, evaluating trade-offs between different modeling approaches

Experience building entity resolution logic, including fuzzy matching, scoring algorithms, and deduplication across data sources

Strong Python skills for data engineering, including batch processing of structured data payloads

Ability to work independently in a fast-paced, staff augmentation setting with an established client team

Nice to Have

Solid experience with Amazon Neptune

Prior experience in fashion, retail, or e-commerce catalogs

AWS certification in databases or data analytics

Experience integrating graph databases with generative AI agents (for example, Amazon Bedrock Agents)

Familiarity with recommendation systems or ranking/weighting logic for content surfacing

#LI-JP3

Our benefits

-Health and dental insurance

-Meal and food allowance

-Childcare assistance

-Extended paternity leave

-Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass;

-Profit Sharing and Results Participation (PLR);

-Life insurance

-Continuous learning platform (CI&T University);

-Discount club

-Free online platform dedicated to physical, mental, and overall well-being

-Pregnancy and responsible parenting course

-Partnerships with online learning platforms

-Language learning platform

And many more!

More details about our benefits here

https://ciandt.com/br/pt-br/carreiras

At CI&T, inclusion starts at the first contact. If you are a person with a disability, it is important to present your assessment during the selection process. See which data needs to be included in the report by clicking here.This way, we can ensure the support and accommodations that you deserve. If you do not yet have the assessment, don't worry: we can support you in obtaining it.

We have a dedicated Health and Well-being team, inclusion specialists, and affinity groups who will be with you at every stage. Count on us to make this journey side by side.

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