2 melhores vagas de full stack developer (python) (Contratando agora!)

Full Stack Developer/Tester
Ben Fatto —Campinas, SP
- Tempo integral
- Home Office
- Azure
- Gestão
- DevOps
Candidatura rápida
8 h
6B13: Senior Platform Engineer - Vaga Afirmativa PCD
mazzatech —Remoto
- Home Office
- Ciência da Computação
- Java
- APIs
- Trabalho remoto
Candidatura rápida
Há 1 dia

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Full Stack Developer/Tester
Ben Fatto —Campinas, SP
Design and develop backend services and APIs in . Demonstrated true full stack ownership: comfortable working across Angular, API design, .
Candidatura rápida
8 h
Backend Developer Generative AI
AllCloud —Rondônia
Collaborate with front-end developers, product managers, and data scientists to deliver end-to-end solutions. Our expertise ensures that clients remain aligned…
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Há 5 dias

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Full Stack Developer/Tester

Ben Fatto -
Campinas, SP

Candidatura rápida

Detalhes da vaga

Tempo integral
Há 8 horas

Qualificações

Ajuste de Desempenho
UI Development
Azure
Gestão
Desenvolvimento Full Stack
DevOps
C#
Certificação AWS
Automação de Teste
.NET
Banco de Dados
OS Kernels
Docker
Graduação
SDKs
REST
Scripting
Angular
APIs
ETL
UI
Inteligência artificial
gRPC
Python
Gestão de identificação e acessos

Descrição completa da vaga

We are seeking an experienced, true full stack Developer/Tester who can own an application end to end: Angular front-end, .NET API and backend services, SQL Server data layer, and automated testing. The ideal candidate is equally comfortable building a UI component, designing an API contract, writing a performant stored procedure, and authoring the test suite that validates all three. This role also integrates agentic AI workflows into the application stack, orchestrating existing AI/LLM services rather than training or fine-tuning models. Candidates should expect to move fluidly across the full stack on any given day, not specialize in a single layer.

Frontend Development (Angular)

Design and build responsive, maintainable Angular applications and components, including state management, routing, and reusable component libraries.
Consume and integrate REST APIs into the UI, handling loading states, error handling, and data validation.
Build UI components that surface agentic AI features (chat interfaces, recommendation panels, agent status/monitoring dashboards, etc.) within existing or new applications.
Collaborate with design/UX to translate requirements into polished, accessible interfaces.

API & Backend Development (.NET)

Design and develop backend services and APIs in .NET (C#), following REST/gRPC best practices for consumption by the Angular front-end and downstream systems.
Architect and implement integration layers connecting Python-based agentic services with .NET applications (via APIs, message queues, or SDKs).
Apply solid software design principles (SOLID, dependency injection, clean architecture) to keep backend services maintainable and testable.
Ensure secure, scalable, and maintainable integration patterns across all application layers.

Database Engineering (SQL Server)

Design, optimize, and maintain SQL Server databases supporting transactional application data and agentic workflow data (logging, agent state, audit trails, metadata).
Write and tune complex stored procedures, queries, indexes, and ETL processes for both application and agentic workflow needs.
Own data model design decisions in partnership with backend and API development.

Testing & Quality Assurance

Build and maintain automated test suites using Playwright for UI and end-to-end testing across the full application stack.
Write unit and integration tests for .NET services and APIs as part of the standard development workflow, not as a separate hand-off.
Develop testing strategies specific to agentic systems (prompt regression testing, output validation, agent behavior testing, edge-case/adversarial testing).
Participate in code reviews, CI/CD pipeline maintenance, and release quality gates.

Agentic AI Integration

Integrate with third-party or internally hosted AI/LLM APIs (e.g., OpenAI, Anthropic Claude, Azure OpenAI, Bedrock, Vertex AI) to power agentic capabilities within applications.
Write Python-based scripts/services for agent orchestration using frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or similar, and wire them into the .NET/Angular application stack.

Cloud & Infrastructure

Deploy, monitor, and manage application services and supporting infrastructure on AWS and/or GCP (e.g., Lambda/Cloud Functions, container services, storage, IAM).
Collaborate with DevOps to ensure scalable, cost-efficient, and secure cloud deployments across the full stack.

Required Qualifications

7+ years of professional experience in .NET / C# development (API and backend services).
7+ years of experience with SQL Server (database design, optimization, stored procedures, performance tuning).
3+ years of hands-on Angular UI development experience, including component architecture, state management, and consuming REST APIs.
Demonstrated true full stack ownership: comfortable working across Angular, API design, .NET backend, SQL Server, and test automation without needing to hand off between specialists.
2+ years of hands-on experience building or integrating agentic AI workflows/systems that orchestrate existing AI/LLM APIs (not model training or fine-tuning).
Experience with Playwright (or similar) for automated UI/end-to-end testing, and writing unit/integration tests for backend services.
Practical experience with agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, Semantic Kernel, or custom agent orchestration).
Proficiency in Python for scripting and AI service integration.
Hands-on experience with AWS and/or GCP cloud platforms for deploying and managing application workloads.
Strong understanding of REST API design and service-to-service integration patterns.
Excellent problem-solving skills and ability to work across the full stack, from UI to database, without silos.

Preferred / Nice-to-Have

Experience consuming LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI, Bedrock, Vertex AI) within application workflows.
Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures as a consumer of these services.
Knowledge of containerization (Docker/Kubernetes).
Experience with prompt engineering and agent evaluation/observability tools.
Background in enterprise application modernization projects that incorporate agentic AI capabilities.

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