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Fullstack ai agent dev senior (node.js + vue.js + claude code)
Seniority: Due to the nature of the position, we are looking for someone with at least 5+ years of experience as a Fullstack Developer, using Claude Code in a daily basis professionally in the SDLC for, at least, 12 months.
To be considered for the role, it is mandatory you to fulfill these requirements:
- Solid back-end development experience with Node.js, RESTful/event-driven APIs, SOLID principles, and clean code practices.
- Solid front-end development experience with Vue.js (Composition API, state management, routing, HTML5, CSS3, JavaScript/TypeScript).
- Experience with reusable component architecture, Design Systems, and UI component libraries (e.g., PrimeVue, eCharts).
- Mandatory, proven experience applying Claude AI across the SDLC (implementation, testing, code review, documentation, maintenance).
- Hands-on proficiency with Claude Code for repository-level tasks, diff reviews, branch workflows, and PR integrations.
- Hands-on experience configuring and managing CLAUDE.md context files, custom subagents, skills, and prompt templates.
- Experience with MCP (Model Context Protocol) integration, connecting AI agents to dev tools, databases, and platform ecosystems.
- Experience setting up CI/CD pipeline automations using hooks and Claude for automated PR reviews and code quality checks.
- Experience with context engineering, task decomposition, and context window management on complex or legacy codebases.
- Solid understanding of cloud-native architectures, Azure cloud infrastructure, Docker containerization, Redis, and MongoDB (modeling, indexing, performance).
- Experience with API management, contract versioning, and end-to-end web security (OAuth2/OIDC, JWT, XSS/CSRF protection).
- Experience implementing automated testing (unit, integration, UI), web accessibility (A11y), performance profiling, and observability (logs, metrics, tracing).
- Building internal automations or agents with Claude Agent SDK / Claude API is considered a strong plus.
Beyond technical knowledge, we also expect you to have a collaborative and team-oriented profile:
- Technical excellence and commitment to writing clean, maintainable, and performant code across back-end and front-end.
- High technical autonomy to drive complex features and AI integrations end-to-end independently.
- Systemic vision to evaluate platform-wide architectural impacts of technical decisions.
- Strong collaboration and communication skills to work closely with UX, QA, DevOps, and multidisciplinary squads.
- Strong teaching ability and mentorship mindset to enable squad members in AI tool adoption without creating single-point dependencies.
- Productive skepticism toward AI: applying critical judgment, mandatory human verification, security checks, and full personal accountability for delivered code.
- Willingness to act as a hands-on Focal Point working directly within squads rather than taking a purely advisory role.
- Proactivity, strong analytical problem-solving skills, and a delivery mindset focused on performance, stability, and UX.
In this role, you will be primarily responsible for driving the structured adoption of AI-augmented software development (SDLC with Claude AI) across technology squads while delivering high-quality, hands-on full-stack web applications and APIs in Node.js and Vue.js.
In a typical week you will:
- Build, scale, and maintain hands-on back-end services (Node.js) and modern front-end interfaces (Vue.js) for high-scale SaaS platforms.
- Act as the team's Focal Point for AI Augmentation, embedding Claude AI across all SDLC phases (implementation, testing, code review, documentation, and maintenance).
- Utilize Claude Code in daily development workflows for repository-level tasks, diff reviews, and pull request management.
- Configure and maintain project context files (CLAUDE.md), defining development standards, guardrails, and acceptance criteria for AI agent usage.
- Create and maintain subagents, skills, and standardized prompt libraries for recurring engineering tasks.
- Integrate agents with internal tools, repositories, task managers, databases, and observability platforms via Model Context Protocol (MCP).
- Implement CI/CD quality automations using hooks and Claude for automated pull request reviews, compliance checks, and test coverage.
- Apply context engineering to large or legacy codebases, managing context window limits and performing systematic output validation.
- Conduct pair programming, developer onboarding, and hands-on enablement to build team capability in AI-assisted workflows.
- Monitor AI adoption metrics (lead time, PR throughput, defect rates) and define clear human-in-the-loop code review criteria.
- Maintain comprehensive documentation for APIs, architecture decisions, component design, and SDLC AI adoption guidelines.
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