Senior AI I Fullstack (Java I Angular) Developer

Jobgether

BrazilYesterday

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Key details

Location
Brazil
Work style
Remote
Level
Senior
Job type
Full-time
Function
Software engineering
Focus area
AI / ML
Posted
Yesterday

Skills

angularartificial intelligenceawsazureci/cdcloud computingcode reviewscontext engineeringgithub copilotgitlabjavajenkinsjirakafkamicroservicesmodel context protocolprompt engineeringquality controlrabbitmqsdlcsoftware architecturesonarqubespringspring boottest automationunit testing

About the role

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior AI | Fullstack (Java | Angular) Developer based in Brazil.

Overview

Join a forward-thinking technology environment where artificial intelligence, advanced software engineering, and intelligent automation are transforming the software development lifecycle. In this senior role, you will lead the integration of AI-powered tools and intelligent agents into engineering workflows, helping teams deliver high-quality solutions faster and more efficiently. You will combine strong Java and Spring expertise with AI orchestration, context engineering, and Spec-Driven Development practices. Working with multidisciplinary teams in the financial services sector, you will help establish technical standards, governance frameworks, and architectural best practices. You will also promote reliable AI-generated code through automated testing, code reviews, and continuous integration. This is an opportunity to shape next-generation engineering practices and drive meaningful innovation in a collaborative, continuously evolving environment.

Accountabilities

    • Lead the technical orchestration of AI tools and intelligent agents throughout the software development lifecycle, improving engineering productivity and delivery quality.

    • Implement and maintain technical specifications and contextual guidance for agent-driven execution using Spec-Driven Development (SDD).

    • Establish engineering governance practices and quality standards for AI-generated code, defining guardrails to minimize technical inaccuracies and unreliable outputs.

    • Explore, implement, and optimize agentic development tools and workflows, including GitHub Copilot, Skills, Model Context Protocol (MCP) integrations, prompt engineering, and context engineering.

    • Guide engineering teams in applying unit testing, automated testing, code reviews, code quality controls, and observability practices.

    • Contribute to the design and evolution of software architectures involving Java, Spring, microservices, messaging systems, and AI-enabled capabilities.

    • Collaborate with stakeholders and multidisciplinary teams to evaluate technical challenges and align architectural decisions with business and functional requirements.

    • Identify opportunities to automate repetitive engineering tasks and improve development workflows through AI-assisted practices.

    • Promote continuous improvement, technical knowledge sharing, and responsible adoption of AI technologies across development teams.

    • Help ensure that AI-enabled solutions meet standards for maintainability, reliability, security, and scalability.

      • Requirements

      • Strong professional experience in software engineering using Java 17 or later and the Spring ecosystem, including Spring Boot and Spring Cloud.

      • Practical experience applying artificial intelligence to software engineering workflows and developing or orchestrating intelligent agents.

      • Solid knowledge of Spec-Driven Development (SDD), context engineering, and prompt orchestration techniques.

      • Hands-on experience with GitHub Copilot, Skills, and MCP integrations.

      • Knowledge of microservices architecture, messaging systems such as Kafka or RabbitMQ, and cloud platforms such as Microsoft Azure or AWS.

      • Experience with unit testing, code quality practices, and CI/CD pipelines using tools such as GitLab, Jenkins, SonarQube, and Jira.

      • Strong understanding of software architecture, development standards, and engineering governance.

      • Excellent analytical and problem-solving skills, with the ability to assess AI-generated code and identify technical risks.

      • Strong communication and collaboration skills, with the ability to influence technical decisions and work effectively across multidisciplinary teams.

      • Adaptability and a continuous improvement mindset, particularly

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