Jobs at CI&T

Senior engineer designing and building cloud-native Java and Python microservices on Azure. Implement secure REST APIs, use Databricks, Spark and Delta Lake for data work, and apply AI-first tools to automate code generation, testing, CI/CD and developer workflows. Mentor teammates, collaborate with architects and stakeholders, and drive engineering productivity and DevOps best practices.

Design, build, and scale production-grade Generative and Agentic AI systems: agent frameworks, RAG pipelines, secure sandboxed execution, observability, automated testing, human-in-the-loop workflows, prompt/versioning, and cloud deployment.

Senior software engineer building cloud-native, AI-first enterprise applications. Own end-to-end microservices, use Azure Databricks/Spark/Delta Lake, automate engineering workflows with AI, mentor teams, and collaborate across product, QA, and DevOps.

Refactor, modernize, and scale existing Python production codebases and data pipelines. Improve architecture, testing, observability, and deployment automation while producing documentation and collaborating with engineering teams to increase reliability and performance of forecasting systems.

Design, build, and operate scalable AWS cloud infrastructure using Terraform and Kubernetes (EKS). Automate provisioning, maintain CI/CD pipelines, optimize performance and cost, implement security best practices, troubleshoot production issues, and document architectures while collaborating with cross-functional teams.

Lead demand generation and ABM for North American industry verticals: translate business priorities into integrated multi-channel campaigns, drive pipeline and revenue, align with sales, measure MQL/SQL/influenced revenue, optimize with data, support events and field marketing, and manage/mentor marketing contributors.

Design, build, and maintain scalable cloud infrastructure on AWS using Terraform and EKS. Automate provisioning, manage container orchestration, develop CI/CD pipelines, monitor performance and costs, implement security best practices, troubleshoot production issues, and document architectures and processes while collaborating with cross-functional teams.

Lead technical design and delivery of Databricks-based data platforms for EMEA clients. Architect and deploy data lakes, meshes, pipelines and data products; scale Spark/Hadoop workloads; implement CI/CD, MLOps and IaC; ensure security and non-functional requirements; collaborate with pre-sales and cross-functional teams; mentor junior engineers and visit clients to bootstrap projects.

Design and implement cloud-native Azure solutions (AKS, Service Bus, Event Hubs, Functions, API Management). Build containerized Java/Spring Boot microservices, enforce standards, conduct code reviews, mentor developers, and implement CI/CD, monitoring, and event-driven messaging architectures while mitigating technical risks.

Lead end-to-end development of data products: ingest, model, transform, validate, and deliver datasets for analytics and AI. Translate business requirements, ensure data quality, build scalable pipelines (SQL/Python/BigQuery), enable AI consumption, and communicate solutions to stakeholders while driving proactive improvements.

Own end-to-end data products: ingest, model, transform, validate, and deliver datasets for AI and analytics. Translate business needs into technical specifications, build SQL/Python pipelines, ensure data quality and monitoring, collaborate with AI teams, and proactively propose improvements while communicating solutions to stakeholders.

Owner of Databricks-based data platform spanning ingestion to dimensional models. Develop and maintain notebooks across medallion layers, implement SCDs and star schemas, manage deployments, monitor and troubleshoot production jobs, enforce code quality via reviews, improve CI/CD and testing, document pipelines, and mentor teammates while collaborating with client stakeholders on architecture and process improvements.

Own and evolve Databricks-based data pipelines across Stage/Bronze/Silver/Gold layers, design dimensional models and SCDs, review code, manage deployments and environments, troubleshoot production jobs, improve CI/CD and testing, maintain documentation, and serve as technical lead and mentor for the data platform.

Lead DevOps practice within an engineering area as an individual contributor: define priorities, drive initiatives, improve CI/CD, cloud infrastructure, container platforms, automation, reliability and observability. Partner with engineering teams to remove blockers, enhance developer experience, influence architecture and operational decisions, and proactively identify risks and opportunities to move delivery forward independently.

Design, build, and optimize cloud-native ETL/ELT pipelines and data lake architectures using Python/PySpark and SQL. Implement partitioning, migrate legacy RDBMS workloads, manage AWS data services (Glue, Athena, Redshift, S3), provision resources with IaC, monitor pipeline health, enforce data governance and quality, and collaborate with analysts, data scientists, and stakeholders to deliver scalable, maintainable data solutions.

Lead design, deployment, and optimization of NVIDIA cuOpt GPU-accelerated routing solutions on Microsoft Azure. Architect scalable, resilient Azure infrastructures, tune GPU performance, establish monitoring and capacity planning, operationalize solutions with Data Science and Platform teams, and provide technical leadership for CUDA and high-performance computing best practices and DevOps automation.

Design, build, and optimize ETL/ELT pipelines and distributed data processing (Python/PySpark) on AWS. Implement data lake architectures, partitioning, and migrations from legacy RDBMS. Monitor pipeline health, ensure data quality and governance, support observability, and collaborate with analysts, scientists, and infra teams to deliver scalable analytics solutions.

Lead design, deployment, and optimization of NVIDIA cuOpt GPU-accelerated routing solutions on Azure. Architect scalable, resilient cloud infrastructures, tune GPU performance, establish monitoring and capacity planning, operationalize solutions with Data Science and Engineering teams, and define GPU acceleration and cloud-native best practices.

Lead design and governance of enterprise master data (counterparties, products, contacts) across multi-platform ecosystem. Assess architecture, define MDM strategy, create data governance, map entities for STP, design Azure-based integration patterns, advise on MDM solutions, collaborate with US technical leads, and produce a long-term data roadmap including Data Fabric and AI-augmented strategies.

Lead design and governance of an enterprise Master Data Management architecture to create a golden source for counterparties, products, and contacts. Assess multi-platform data flows (Salesforce, NetSuite, trading/ERP systems), define integration patterns on Azure middleware, build data governance and stewardship frameworks, map entities for straight-through processing, advise on MDM solutions, and deliver a long-term data roadmap including lineage and AI-augmented strategies.