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Solutions Architect (AI)
Описание вакансии
Текст:
TL;DR
Solutions Architect (AI) (Java, AWS, DataHub): Leading solution and platform architecture for complex DataHub and mapper integrations with an accent on distributed systems, cloud-native platforms, security, and scalability. Focus on designing RFCs and reference architectures, applying AI-native engineering with agents and LLMs, and improving reliability, performance, and cost across global teams.
Location: Remote, Brazil-based, São Carlos
Company
is a global data and technology company operating across financial services, healthcare, automotive, agribusiness, insurance, and other markets, with 25,200 employees across 32 countries.
What you will do
- Own solution and platform architecture for complex DataHub and mapper initiatives, including RFCs, reference designs, and scalable solutions.
- Bridge enterprise priorities and the Brazil-based DataHub squad while aligning stakeholders across global regions.
- Lead architecture reviews and guide cross-team technical decisions.
- Drive secure platform development, deployment practices, performance, reliability, and cost optimization.
- Apply AI-native engineering patterns, including agents, LLMs, MCP, and agentic workflows.
- Mentor engineers and improve observability, incident response, inner-source practices, and integration reuse.
Requirements
- Strong experience in software engineering, solution architecture, or platform engineering in complex environments.
- Expertise in system design, distributed systems, and large-scale backend architectures.
- Experience with Java, Spring Boot, microservices, OpenAPI, AWS, Kubernetes/EKS, containers, and cloud-native architectures.
- Experience with CI/CD, Jenkins, release strategies, security architecture, and code quality tools such as SonarQube, Veracode, or Checkmarx.
- Experience leading architecture discussions, writing RFCs, and influencing technical decisions across teams.
- Advanced English is mandatory; Portuguese is required for local collaboration.
Nice to have
- Machine learning serving, pipelines, or MLOps experience.
- Hands-on experience with AI-native tools, LLMs, MCP, or agent-based workflows.
- Infrastructure as code, advanced cloud automation, Kafka, event-driven architectures, RAG, or evaluation frameworks.
- Experience with large-scale global platforms and inner-source collaboration models.
Culture & Benefits
- People-first, inclusive, and purpose-driven culture.
- Global collaboration across 32 countries and multiple business markets.
- Equal opportunity and affirmative action workplace.
- Affinity groups supporting LGBTQIAPN+ employees, racial equity, gender equity, people with disabilities, and cross-generational inclusion.