Azienda in resistente crescitaSettore AI Azienda Piattaforma all'avanguardia nell'Intelligenza Personale ed Enterprise basata su AI. Progettano sistemi che unificano fonti di dati e flussi di lavoro eterogenei tra le principali suite di produttività (Microsoft 365, Google Workspace) e le applicazioni aziendali (Slack, Salesforce). La loro missione è aumentare la produttività organizzativa e individuale attraverso l'automazione intelligente e l'AI contestuale. Offerta
Service Development & Architecture: Design, implement, and deploy microservices and APIs using Python, focusing on scalability, resilience, and maintainability. API Integration: Develop and maintain robust RESTful APIs and asynchronous event-driven services (e.g., using Kafka or RabbitMQ) for internal and external consumption. Data Engineering & AI Pipelines: Contribute to the design and implementation of data ingestion, transformation, and processing pipelines. Integrate machine learning models and LLM-based functionalities into backend services. Database Management: Work with relational (e.g., PostgreSQL) and/or NoSQL databases, including schema design, query optimization, and performance tuning. Experience with vector databases for AI applications is a strong plus. Infrastructure & Deployment: Collaborate on CI/CD pipelines (e.g., Jenkins, GitLab CI) and container orchestration (e.g., Docker, Kubernetes). Support cloud infrastructure management (AWS). Code Quality & Practices: Promote sound practices in coding, testing (unit, integration, end-to-end), and deployment. Conduct thorough code reviews and mentor junior engineers. System Observability: Implement monitoring, logging, and alerting solutions to ensure system health and performance. Security: Adhere to security practices in API design, data handling, and infrastructure deployment.
Competenze ed esperienza
4/5+ years of professional experience in backend software development. Python Expertise: Deep proficiency in Python, with experience using relevant frameworks (e.g., Flask, FastAPI, Django). API Design & Development: Proven experience designing and implementing complex RESTful APIs, with a solid understanding of API versioning strategies. Familiarity with GraphQL is a plus. Database Technologies: Strong experience with relational databases (e.g., PostgreSQL) and/or NoSQL databases (e.g., MongoDB, DynamoDB). Cloud Computing: Hands‑on experience with at least one major cloud provider (AWS preferred). Understanding of serverless architectures and managed services. Version Control: Expert‑level proficiency with Git and collaborative development workflows (e.g., GitHub, GitLab). Software Design Principles: Solid grasp of SOLID principles, design patterns, and microservices architecture. Testing Frameworks: Experience with Python testing libraries (e.g., pytest, unittest). Communication: Excellent written and verbal communication skills in English, with the ability to articulate technical concepts clearly.
Nice to have
Experience with Go or Node.js for specific microservices. Familiarity with message queues (e.g., Kafka, RabbitMQ, SQS). Exposure to container orchestration technologies, including Kubernetes. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and LLM integration (e.g., LangChain, OpenAI API). Knowledge of vector databases (e.g., Pinecone, Weaviate, Qdrant) and their application in search and recommendation systems. Experience with CI/CD tools and practices (e.g., Docker, Jenkins, GitLab CI).
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