SRE Specialist, Agro Retail Community

Itaú Unibanco

Especialista SRE no Itaú, maior banco privado da América Latina, construindo plataformas escaláveis e resilientes. Liderando arquitetura cloud-native e adoção de IA Generativa para produtos financeiros.

Posted 8/13/2026full-timeSão Paulo • 🇧🇷 BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in defining and evolving technology vision, leading architectural decisions, and driving technological modernization, particularly in AI and cloud environments. Proficient in evaluating AI models and implementing best practices for software quality and DevSecOps.

Highest-signal resume keywords

Architecture And Development Of Distributed SoftwareExpertise In Java, Spring Boot, MicroservicesExperience In AWS Cloud EnvironmentsHands-On Experience In Developing Products With Generative AIStrong Experience With CI/CD And DevSecOps Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

JavaSpring BootMicroservicesAPIsBFFsEvent-Driven ArchitecturesRelational DatabasesNoSQL DatabasesGenerative AICI/CD

Soft Skills

Technical LeadershipCollaborationInfluencing Strategic Decisions

Tools & Technologies

AWSInfrastructure As CodeDevSecOpsLangChainLangGraphSemantic KernelCrewAIAzure AIBedrockVertex AI

Industry Keywords

AI-First PracticesCloud MigrationLegacy System TransformationGovernanceObservabilitySecurityMonitoringRAG ArchitecturesAI WorkflowsModel Observability

Tech Stack

Tools & technologies

AWSAzureCloudJavaNoSQLOpen SourcePythonSpringSpring BootSpringBoot

About the role

Key responsibilities & impact

Define and evolve the short-, medium- and long-term technology vision for the Agro Retail community
Collaborate with GPMs and GTMs, ensuring technical feasibility and sustainability of solutions
Lead architectural decisions for scalable, reusable, product-oriented platforms
Ensure adoption of corporate standards, reuse, technological simplification and single custody of assets
Drive technological modernization, cloud migration and legacy system transformation
Lead the adoption of AI-First practices in digital products and corporate platforms
Define strategies for the use of Generative AI across the entire product development lifecycle
Evaluate and select AI models and LLMs considering effectiveness, cost, latency, scalability, privacy and compliance
Define standards for integrating LLMs, RAG, AI agents, copilots and intelligent workflows
Lead proofs of concept and decisions on proprietary and open-source models
Ensure governance, observability, security and monitoring of models in production
Identify AI opportunities in customer journeys, internal processes and engineering
Serve as a technical reference for engineers and architects
Influence strategic decisions and promote the technical development of teams
Lead software, data and enterprise integration architecture discussions
Prepare technical assessments on technology risks and information security
Promote engineering excellence, observability, software quality and DevSecOps
Define cloud-native architecture standards
Lead initiatives involving AWS, microservices, containers, serverless and distributed platforms
Promote FinOps, automation and efficient cloud resource management
Contribute to the evolution of data, analytics and artificial intelligence within the community

Requirements

What you’ll need

Strong experience in architecture and development of distributed software
Expertise in Java, Spring Boot, microservices, APIs and BFFs
Experience with event-driven architectures and mission-critical systems
Experience in AWS cloud environments
Advanced knowledge of relational and NoSQL databases
Strong experience with CI/CD, Infrastructure as Code and DevSecOps practices
Experience in technical leadership and defining engineering standards
Hands-on experience in developing products with Generative AI
Knowledge of LLM fundamentals and architecture
Experience evaluating and selecting models such as GPT, Claude, Gemini, Llama and Mistral
Knowledge of frameworks such as LangChain, LangGraph, Semantic Kernel and CrewAI
Experience with RAG architectures, AI agents and AI Workflows
Knowledge of prompt engineering, response evaluation, AI metrics and model observability
Ability to analyze trade-offs between cost, performance, accuracy and scalability
Experience with Python applied to AI, Machine Learning or automation is a plus
Knowledge of enterprise AI platforms including Azure AI, Bedrock and Vertex AI

Benefits

Comp & perks

Transportation allowance (Vale-Transporte)
Meal allowance (restaurants) / Food allowance (supermarkets)
Medical plan (Fundação Saúde Itaú or Central Nacional Unimed)
Dental plan (Odontoprev or Interodonto)
Life insurance
Profit Sharing (PLR) — participation in profits and results (subject to the bank's performance)
Private pension plan
Exclusive discounts on our financial products
Extended maternity and paternity leave
Childcare / Babysitter allowance (for parents)
Education support
Wellhub or TotalPass
Access to Itaú leisure clubs (Guarapiranga / Itanhaém and São Sebastião)
Additional benefits you may learn about during the process